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I

Preface Today’s business environment characterized by out of control changes, unexpected crises, faster flow of information, increasing complexity and pervasive globalization, requires logistics and supply chain transform towards more optimized and robust paradigms; resulting in such paradigms needs sustainable innovativeness in design, process, organization and technology. Logistics is a key enabler of supply chain collaboration, thus minutely optimized processes in this field allow supply chains to increase their efficiency respectively. In this context, an important task of process optimization is to find innovative methods and approaches which enhance logistic structures and supply chains for a better and more efficient fulfillment of customer needs. Efficiency is the real driving force for process optimization. The objective of the process optimization methods is the methodical monitoring, efficiency measurement and optimizing, to enable continuous individual and enterprise-wide performance supervision. In recent years, research has made an extensive contribution in solutions and methods of process optimization in logistics. This volume provides valuable insights into novel concepts in process optimization and supply chain efficiency by taking into account transport logistics and Inter-modal transportation as well as green approaches in logistics and supply chain management and globalization problems. Innovative research-based process optimization methods and solutions need to be validated by real world applications as a prove to meet the needs of practitioners. Therefore this volume also presents the cases and examples from practice contributing to an innovation-oriented strand of research. Furthermore, this book contains international contributions to topics as supply chain design, supply chain integration, supply chain performance analysis and information technology, such as radio frequency identification, and approaches to simulate efficient supply chain networks. We would like to thank the authors for their excellent contributions, which advance the logistics research progress. Without their support and hard work, the creation of this volume would not have been possible. Additional thanks go to the publishing company, the Erich Schmidt Verlag, especially to Dr. Joachim Schmidt for the opportunity to publish this volume and his valuable co-operation. This book would not exist without good organization and preparation. Thus, we would like to thank Sara Kheiravar, Thorsten Lammers and Sebastian Brockhaus for their efforts to prepare, structure, and finalize this book. Hamburg, July 2010

Prof. Dr. Thorsten Blecker Prof. Dr. Dr. h. c. Wolfgang Kersten Prof. Dr. Christian Lüthje V

Table of Content Preface ......................................................................................................... Table of Contents .....................................................................................

V VII

I. Innovative Technological Solutions A RFId Web-Based System for Increasing Visibility along the ThermoMechanical Supply Chain ............................................................................ Tommaso Rossi and Margherita Pero

3

A Structural Analysis of Information Technology (IT) Integration in Food Supply Chains and Firm Innovativeness.................... Suhana Mohezar and Claudine Soosay

17

Risk Analysis in Production Systems with Random Yields and Rigid Demand ................................................... Winston Po and Rachel Green

33

Logistics Carbon Footprinting in Practice ................................................. Christian Wick and Matthias Klumpp

41

II. Learning from Practice-Case Analyses in Logistics Spanish Logistics and Trade ...................................................................... Sami Bensassi, Laura Márquez-Ramos, Inmaculada Martínez-Zarzoso, Celestino Suárez-Burguet

65

Business Processes and Logistics Service Competenciesof Logistics Service Providers in China ................. Ming J. Ding and Booi H. Kam

81

Managing Production Ramp-ups in the European Automotive Supply Chain – The Supplier´s View .......... Tobias Held

99

The Role of Consumer Insight in New Product Development and Its Impact on Supply Chain Management: A Swedish Case Study .. David Eriksson and Per Hilletofth

113

The Balanced Scorecard as a Measure of Performance: A Case Study on a Shoe Industry Sector ................................................. Leonardo Perazza, Paulo Cesar Chagas Rodrigues

127

VII

Table of Content

Case Study on Inventory Management in a Small Manufacturer of Auto Parts .................................................... Nicolle da Silva Panzuto and Paulo Cesar Chagas Rodrigues

145

III. Optimization methods in Transportation Processes Intermodal Transportation........................................................................ Katharina Grobleben Programming Tools, an Alternative to Optimize the Logistics at the Transportation Process of the Oil Palm Fresh Fruit Bunches (FFB) ....... Carlos A. Fontanilla, Wilson Adarme, Martin D. Arango Modelling Freight Flow Information within the Maritime Transport Chain: Benefits and Effects of „Estimated Time of Arrival“ (ETA) Messages .. Ralf Elbert, Arzum Oezgen, Fabian Walter 3E Logistics – Electric Transport Routing............................................... Matthias Klumpp, Sascha Bioly, Tristan Keusgen

165

179

193 207

Improving the Efficiency of Rail-Based Hinterland Transport by the Means of Advanced Extended Gateway for Rails ........................ Hans G. Unseld and Herbert Kotzab

221

Evaluation of Telemetry Implementation Benefits for a LPG Distribution Company .............................................. Abdelkhalek Nakabi and Zitouni Beidouri

235

IV. Performance Enhancements in Modern Supply Chains A Genetic Algorithm of Supply Chain Performance Analysis, Focusing on Information Delay ............................................................... Asadollah Najafi, Abbas Afrazeh, Heinz Bartsch

250

The Influence of Agile and Resilient Practiceson Supply Chain Performance: An Innovative Conceptual Model Proposal ..................... 265 Susana Garrido Azevedo, Helena Carvalho, V. Cruz Machado, Fernado A. Grilo Performance Management of Supply Process Chain with Application to the Coatings Industry ............................................... Noura Abdelmalek, Tareq Issa, Mohammed Hajeeh

VIII

283

Table of Content

Evaluation of Variant-Driven Logistics Complexity in the Automotive Industry: Development of Key Performance Indicators for an Evaluation Approach of Impacts caused by Product Variety in Inbound Logistics ..................................... Axel Wagenitz, Annika Lechner, Bernd Hellingrath Container Transshipment Simulation and Efficiency Analysis ............... Matthias Bode, Felix Hofmann, Volker Berkhahn

299 321

V. Innovative Approaches in Supply Chain Design Early Supplier Involvement into New Product Development – The Right Point of Time as Precondition for Success ............................. Melanie Serafin, Stefanie John, Kai-Ingo Voigt

339

Production Ramp-up in Supply Chains for Innovative Products Providing Global Objectives .................................................................... Jerome Quick and Tim Renner

355

Green Logistics: An Innovation for Logistics Products?......................... Wolfgang Kersten, Claudia Allonas, Sebastian Brockhaus, Nikolaus Wagenstetter Mixed/Integer Linear Programming, Silver-Meal & Economic Order Quantity: Efficiency versus Popularity Tania Rodríguez and Carlos Sierra Ramp-up Management a Chance for Job Production? ............................ Henning Strubelt and Hartmut Zadek

369

387 403

IX

I. Innovative Technological Solutions

A RFId Web-Based System for Increasing Visibility along the Thermo-Mechanical Supply Chain

Tommaso Rossi and Margherita Pero

Abstract This paper presents a case study of an application of an innovative system integrating RFId and web-based technologies in an Italian leading company manufacturing vessels and tube heat exchangers. The system allows for sharing information on its shop floor activities among the actors of the supply chain, i.e. clients and suppliers. The main technologies used are: RFId transponder to identify either one component, or an operator, or a tool, e.g. welding machine, or a production phase, a Wi-Fi network, to communicate the data, and a web based application accessible also by the clients of the company. This paper shows the methodology used to define the best architecture of the system and the technical solutions adopted to practically implement the system. Moreover, benefits in terms of efficiency and effectiveness of the application have been observed: reduction in cost for quality control, production progress and hours worked control. On the other side, a qualitative advantage is the increase in the visibility of production progress to the customers, since it is perceived as a valuable service by the customers.

Keywords: ETO, supply chain, visibility, RFId, web-based platform

1 Introduction and background The lack of coordination among the nodes of a supply chain results in several drawbacks, i.e. increase of manufacturing costs, inventory costs amplification, longer replenishment lead times, increase of transportation costs, growth of the labor-cost for shipping and receiving (Forrester 1961, Sterman 2000, Chopra and Meindl 2001). In spite of the above mentioned drawbacks, the lack of collaboration is often experimented in real-life industrial environments due to either behavioral or information processing hurdles (Forrester 1961, Sterman 2000). Behavioral hurdles are: (i) the tendency of each supply chain node to consider its actions locally and to react to the current local situation rather than identify the root causes; (ii) the inability of each stage to learn from its actions, since the most relevant impacts (of the actions) occur elsewhere in the chain; (iii) the lack of trust among supply chain 3


partners which causes opportunistic ways of doing at the expense of overall logistic network performance (Chopra and Meindl 2001). Information processing hurdles are: (i) forecasting based on orders by downstream nodes instead of on the final customer demand (ii) the lack of information sharing, i.e. low visibility along the supply chain (Caridi et al. 2009). Visibility is “the ability to access/share information across the supply chain and to use it in real time” (Swaminathan and Tayur, 2003). The more accurate, trusted, timely, useful, and in a readily usable format is the information exchanged the higher the visibility (Gustin et al., 1995; Mohr and Sohi, 1995; Closs et al., 1997). It should also noted that: “Supply chain visibility does not mean sharing all information with all partners in the supply chain, but rather that the shared information should be relevant and meaningful. End-to-end visibility can be defined as the sharing of all relevant information between supply chain partners, also over echelons in the chain” (Kaipia & Hartiala, 2006). In this paper we will focus on how to overcome information processing hurdles in Engineer-To-Order (ETO) supply chains. An ETO supply chain is a supply chain where the ‘decoupling point’ is located at the design stage, so each customer order penetrates the design phase of a product (Hicks et al. 2000), the development and production of ‘one of a kind’ products falls under this category. Since in ETO contexts, no activity is performed based on forecasts, the main information processing hurdle to be analyzed is the lack of information sharing. Effective information sharing has been recognized as a key source of competitive advantage for ETO companies (Hicks et al. 2000). By boosting the integration and the communication among the main actors involved in the order-to-cash process in ETO firms, i.e. product division, production, engineering department, purchasing, suppliers and client, the lead time to engineer and produce the product is reduced, by reducing the reworks required (Caron and Fiore, 1995). IT systems could be powerful tools to support such an integration. Various IT system architectures for ETO firms have been proposed. Hicks et al. (2000) suggest the use of common databases that support tendering, design, procurement, and project management to integrate the different processes of the firm. Karkkainen et al., (2003) propose a peer-to-peer architecture integrated with RFId for controlling material flows in large investment project. As far as production control systems are concerned, Bertrand and Muntslag (1993) and Little et al. (2000) suggest that the characteristics of an ETO system should diverge from MRP-based ones, therefore they propose production control systems that take into account the high level of uncertainty and customer specific product specifications. Notwithstanding the relevance of these contribution, the review of the literature on ETO supply chain management by Gosling and Naim (2009) outlines that many questions are still left unresolved in the realm of information management for ETO supply chains, among the others: “Which IT systems are most suitable for the ETO sector?”. To shed more light on this topic, in this paper, we present a case study of an application of an innovative system integrating RFId and web technologies for 4


increasing visibility in a ETO supply chain. In particular, the case of the thermomechanical industry has been analyzed. The remainder of the paper is organized as follows: section 2 presents the proposed solution, discussion over the benefits of the solution are depicted in section 3. Conclusions and direction for future research are outlined in section 5.

2 Case study The analyzed case study refers to the thermo-mechanical industry. In particular we focus on a supply chain which concurs to design and build plants for generating and exploiting thermal power.

2.1 The supply chain The firm considered in our case study is an ETO manufacturer, who directly supplies the general contractors responsible for the whole plants construction with vessels and tube-heat exchangers. The company, through its purchasing department, buys materials, basically sheet metal, tubes, flanges, etc., by several second-tier suppliers. The characteristics of such materials (e.g. kind of metal, thicknesses, external and internal diameters) are defined by the company’s engineering department on the basis of the general contractor’s specifications. These specifications drive the engineering department also in performing the detailed design of the vessels and/or heat exchangers to be supplied. On the basis of the detailed design, of the materials characteristics, of the technologies available in the machine shop (basically cutting, bending, welding, etc.) and of the operators’ skills, the company’s technical department defines the production cycle, which allows the requested vessels and/or heat exchangers to be produced. Finally, once the production cycle has been drawn and the needed materials are available, the production of the single vessel or heat exchanger can start. It finishes when all the production phases of the corresponding production cycle have been completed and all the requested quality controls on semi-finished products, sub-assemblies (i.e., in the case of vessels, shell and, in the case of heat exchangers, shell, tube-bundle, shell-side and tube-side) and on the finished vessel or heat exchanger have been passed.

2.2 The relevant information to share For outlining the information that the focal company should share, several interviews has been done. These interviews involved both some of the focal company’s customers and some of the companies belonging to the Italian association of general contractors, which operate within the thermal power plants supply chain. Such interviews show as customers and potential customers are particularly interested, on the one hand, in real-time data on the completion status of their orders and, on 5


the other hand, in information to trace all the materials, which compose the item they requested, as well as in information about the quality controls the materials have been passed. They claim that these information, if available in real time, should enable process and service level improvements. For instance, they are the basis for shared production plans definition. Additionally, since general contractors can monitor the state of their orders, they can update their plans on the basis of the state of the order in the supplier plant, or can decide to which supplier place a new order given the state of capacity saturation of the suppliers.

2.3 The proposal To allow the focal company for sharing the above mentioned information, we propose a system composed of two sub-systems. The first is aimed at gathering from the field the completion, quality and traceability data; the second is devoted to give visibility on the proper data to each customer.

2.3.1 Data gathering sub-system For being completely processed, the customer order should go through the processes of engineering, purchasing and production. As a consequence, this sub-system, besides the data concerning the order completion status, the quality controls passed and the materials traceability along the production process, should be able to gather data about the order completion status also from the engineering and purchasing processes. In developing the data gathering sub-system we started from the part we believe is the most complex one, i.e. the part devoted to collect data from the machine shop in real-time and in a way as more automated as possible. As a consequence, hereinafter we refer to the data gathering system from the production process. For monitoring all the materials, which move along the company’s production process, all of them must be univocally identified. Moreover, since the company wants to reduce as much as possible the operators’ intervention in collecting data from the field, the meta-decision was to base the data gathering sub-system on RFId, i.e. on one of the most widespread auto-identification technologies. In particular, the basic idea is to identify each material, production resource and operator within the machine shop and each phase of the production cycle with a RFId transponder. The most complex issue was to define how to fasten a RFId transponder to each material, which moves along the machine shop. To do this, in the present case study the following analysis has been performed. For each sub-assembly realized in the machine shop all the materials it is composed of have been identified and, for each of them, its characteristics in terms of material kind, shape and production phases it can be subjected to have been outlined. In table 1 the example concerning the ‘shell’ sub-assembly is shown. 6

A RFId Web-Based System for Increasing Visibility along the Thermo-Mechanical Supply Chain Material s

Production phases

Sheet metal

Cutting (edge temperature: about 100 °C)

Material kind

Shape

Bevel (edge temperature: about 1,700 °C) Grinding (such a phase is performed on the edge) Bending Welding (temperature in proximity of the welding point: about 1,500 °C) Cladding (temperature on the sheet metal surface: about 200 °C) End plate

Cutting (temperature in proximity of the hole: about 1,500 °C) Bevel (edge temperature: about 1,700 °C) Welding (temperature in proximity of the welding point: about 1,500 °C) Cladding (temperature on the end plate surface: about 200 °C)

Nozzle Flange

Carbon steel alloy Nickel alloy Stainless alloy (non ferrous alloys are used; however the non ferrous materials are less then the 5% of the materials in the company’s machine shop)

The thickness ranges from 5 mm to 350 mm (the thickness of non ferrous materials ranges from 20 mm to 40 mm) Surfaces are characterized by roughness

Metalwork (when the material is on the machine no other objects can be fastened to it. After the metalwork the surface of the nozzle or the flange is covered by mineral oil) Welding (temperature in proximity of the welding point: about 1,500 °C) Cladding (temperature on the nozzle or flange surface: about 200 °C)

Tab. 1: Characteristics of the materials, which move along the company’s machine shop

Due to the high temperature reached by the edges or by the surfaces of the materials during some of the production phases and due to the fact that during metalwork no foreign body can be into the machines, it is clear that the RFId transponders must be removed from the materials at the beginning of each production phase and must be fastened again to the corresponding materials once the production phase is completed (see also the section devoted to describe how the RFId-based data gathering sub-system works). As a consequence, a method for easily fastening and removing transponders to and from materials is needed. Due to the very wide range of thickness outlined in table 1, the edge cannot be used as junction between the material and a case for transponders provided with compression spring. Moreover, since the roughness of the materials surfaces and since the materials after metalwork are covered with mineral oil, also the use of adhesive cases for the transponders is not an option. Then the decision has been to fasten transponders by means of cases on which it is possible to install magnets (for the majority of the materials, 7


which move along the company’s machine shop) or compressions springs (for the 5% of non ferrous materials, whose thickness is quite small; see again table 1). Due to the outcomes of the analysis of the production phases the materials can be subjected to, it has been possible to specify how the RFId-based data gathering sub-system should work. In particular, the phases to control the state of the production activities have been defined as follows. When an operator starts to carry out a production phase, he takes the RFId transponder identifying himself, the one identifying the production phase he is performing, the RFId transponder identifying the production resource he has to use if necessary and finally the one of the material involved into the production phase. It is worth noticing that if the production phase is a welding phase, two materials are involved in it. In this case, the RFId transponder of each material must be taken by the operator and a transponder where the welding code has been recorded must be given to the operator by the foreman. All these transponders are then placed by the operator on a RFId reader, which transmits via Wi-Fi to the company’s database the codes of the various transponders and the company IT system records into the database the actual day and time, i.e. beginning of the production phase. When the operator has completed the production phase, the operator took away from the RFId reader his transponder along with the transponder of the production phase and he replaces the phase transponder on the blackboard inside his working area. The RFId reader transmits via Wi-Fi to the company’s database the signal that the production phase has been completed along with the actual day and time. Therefore in the database it is possible to read that the phase has been completed. When the materials can be downloaded from the machine they are placed, the operator place the transponder of the machine back on it, and the one of the materials (when other operations can be done on them) too. When this happens, the RFId reader, free of the transponders of the machine and the components, transmits to the database actual date and time of this action. This means that the machine can be used for another operation. The data gathered are grouped in the database presented in table 2. The system gathers also data from quality control. Since no criticalities involving the RFId transponders are connected to quality control activities (see again table 1), the phases, which allow for such data gathering, have been defined as follows. The operator has a quality control plan where all the quality controls he has to perform and the corresponding bar-codes are listed. The operator logs in the palm, which is able to read both RFId transponders and bar-codes and, then, by reading the bar-code printed on the plan, identifies the quality control he should perform.

8

A RFId Web-Based System for Increasing Visibility along the Thermo-Mechanical Supply Chain Field

Data coming from:

Operator looking after the machine

From the transponder identifying the operator

Phase

From transponder identifying the phase

Tooling machine used for the phase

From transponder identifying the machine

Date and hour of beginning and end of production and machine release

Automatically, since the RFId reader transmits the codes of the

Note

Production cycles are divided into pre-defined phases and each phase is identified by a transponder

Transponders of the operator, phase, machine and components Contract

Automatically, since the RFId reader transmits the codes of the transponders of the components

There should be a database in the IT system to link components to the other elements

Customer code

Automatically, from IT system by reading the transponder of components


Order

Automatically, since the RFId reader transmits the codes of the


transponders of the components Sketch


Position


Component 1 Component 2

There should be a database in the IT system to link components to the other elements There should be a database in the IT system to link components to the other elements

From transponder identifying the component

… ID welding

From transponder named by the foreman

Tab. 2: Database for production control

9


By means of the palm, he reads the RFId transponder of the material, which is the object of the quality control. The information regarding the operator, the phase and the object are send via Wi-Fi to the database. The operator performs the quality control and inserts in the palm the result. Then he transmits the result to the database. The data gathered are grouped in the database presented in table 3. Field

Data coming from:

Operator of quality control

From log-in in the palm by the operator

Phase of the control plan

From bar-code of the phase printed on the control plan

Quality plans are divided into predefined phases and each phase is identified by a bar code

Date and hour of beginning of control phase

Automatically, from IT system due to information sent via the palm

This is possible if the phases printed on the control plan have a bar-code that identifies the beginning and one that identifies the end.

Contract



Customer code



Order



Sketch



Position



Component 1

From transponder identifying the component

Component 2

Note

Component n Date and hour of end of control phase

Automatically, from IT system due to information sent via the palm

This is possible if the phases printed on the control plan have a bar-code that identifies the beginning and one that identifies the end.

Tab. 3: Data base of the data gathered for quality control

Besides the choice of how fastening the transponders to the materials and the specification of how the RFId-based data gathering sub-system works, for completely defining the sub-system it is necessary to select the radio frequency, on which it must be based. The two candidate radio frequencies are HF (high frequency) and UHF (ultra high frequency). The UHF-NF (UHF near field) has not been considered since for being read the transponders are removed from the materials and, 10


then, the reading is performed not in presence of relevant metal masses. HF is preferred to UHF due to the fact that, on the one hand, for being read the transponders are directly placed on the RFId reader, i.e. reading transponders at a considerable distance is not requested, and, on the other hand, into a context characterized by the presence of relevant metal masses and magnetic cases HF is more reliable than UHF.

2.3.2 Data sharing sub-system To share with the customers the data gathered by means of the RFId-based subsystem the idea is to collect the data, i.e. the databases shown in tables 2 and 3, into a server connected to the LAN (local area network), which works as repository for a web-platform. Via internet, by means of user name (the code assigned by the company to the customer) and password (chosen by the customer), all the company’s customers can have access to the web-platform. In other words, they can have access to a service, which allows for showing in a user-friendly way the data recorded into the databases of the completion level of the orders (table 2) and of the quality checks passed by the materials (table 3) as well as into the traceability database (table 2). Obviously, each customer can see the portions of the databases, which refer to its orders only. This is possible due to the key represented by the customer’s code. As a matter of fact, such a code, which must be entered by the customer to access the web-platform, is present both in the database depicted in table 2 and in the database depicted in table 3. Here it is worth noticing that the web platform is perceived as a source of higher competitive advantage of the whole supply chain, since it allows for storing and showing to general contractors the features and the origin of each material used for satisfying their orders. Moreover, through the web platform, additional value-added services should be proposed to general contractors, e.g. they can be alerted in advance of quality controls they want to supervise, that increase clients fidelity. The architecture that allows for gathering the data from the field and for sharing them is depicted in figure 1.

11


general contractors’ clients

internet

company’s server server

Wi-Fi company’s rete Wi‐Fi network

RFId/barpalmare code palm

RFId/bar‐code

bar‐code di fase quality control diactivity collaudo

RFId dispositivo reader RFId fisso

input da input from the operatore operator

transponder material componente

transponder production fase di lavoro phase

transponder operator transponder material machine transponder macchina operatore componente

Fig. 1: Architecture of the system

3 Discussion Several benefits are connected to the adoption of the above described system. In particular, they can be measured from the company’s perspective or from the supply chain’s one. With reference to the first, benefits have been measured both in terms of revenues and costs. In facts, the revenues of the company that implemented the system has grown. This has been connected to increasing customer fidelity and attraction of new customers. On one side, sharing data with the customers on the orders completion status, on the quality controls passed by the materials and on the materials traceability allows the company for improving the service level assured to the customers and, as a consequence, the customers’ willingness to buy 12


from the firm. On the other side revenues of the company rise also thanks to the visibility on the placed orders which the company is able to guarantee that can attract new customers resulting in a further increment of the revenues. Moreover, operational costs reduced. The adoption of the system described in the previous paragraph and, in particular, of the RFId-based data gathering subsystem implies, as by-product, the automation of the control of the orders execution as well as of the materials traceability along the company’s production process. This means that activities, such as analyses in field for understanding the completion levels of the different orders processed within the machine shop or for identifying which material has been assembled into which sub-assembly, must not to be performed any more. As a consequence, the yearly operational costs reduction can be quantified according to the costs for the company of these activities. In the case under study, the yearly savings connected to the activities, which the company need not to do due to the sub-system, are about half of the initial investment for the hardware and the implementation of the RFId-based data gathering sub-system. The advantages connected to the supply chain’s perspective, i.e. the advantages in terms of revenues for both the company and the whole supply chain, are quite difficult to be evaluated. However, the rise of the revenues does not involve the company only, but the upstream supply chain actors too. As a matter of fact, the higher the number of orders placed to the focal company, the higher the number of orders the focal company places to its suppliers. Clearly, if all the companies belonging to the thermal power plants supply chain adopted the RFId-based data gathering sub-system the savings in their operational costs could also result in benefits for the whole supply chain in terms of revenues. As a matter of fact, more efficient are the activities performed within each single company of the supply chain, more competitive is the whole supply chain and, as a consequence, the higher the service level of the whole supply chain and the more attractive is the supply chain for both the present and potential customers.

4 Conclusions The case study presented in this paper allows for drawing two different types of concluding remarks. The first refers to the interest of the actors belonging to the thermo-mechanical supply chain in sharing information. The performed interviews outline the high interest of the general contractors responsible for the construction of plants for producing and/or exploiting thermal power in receiving real time data on their orders completion status, on the quality checks passed by all the materials their orders are composed of, as well as on the materials traceability. This means that thermo-mechanical supply chain focus should enlarge: they should not be any more just suppliers of products but they should work to be suppliers of products and services. Due to the nature of the required services, i.e. sharing real time data, the proposal presented in the case study, i.e. gathering data from the field by means 13


of the RFId technology and sharing such data through a web platform, can be generalized for the whole thermo-mechanical supply chain. Moreover, it is also possible to state that the interest of general contractors in obtaining the above mentioned information results in advantages for the whole supply chain, which is able to satisfy such requirements. In particular, besides the increment on the supply chain revenues due to the new value added services the supply chain is able to provide, each supply chain’s actor, who implements the system proposed in this work, experiments a reduction of the operational costs (see section 3). This allows the whole supply chain for being more competitive also from the efficiency point of view and, then, for being more attractive for general contractors (originating a positive loop on the supply chain revenues). The second type of concluding remarks concerns the methodology for defining the RFId-based data gathering sub-system for a generic actor of the thermomechanical supply chain (see figure 2). Such a methodology should be composed by the same steps performed for identifying the RFId-based data gathering subsystem of the present case study. In particular, the first step is the identification of the data it is necessary to gather from the field. In a case similar to the one faced in the present study they are represented by the information that must be shared. The second step refers to the analysis of the characteristics of all the materials to which the RFId transponders must be applied for gathering the previously identified data. The characteristics to be investigated are the ones concerning the production phases the materials must be subjected to as well as the ones referring to the types and shapes of the materials. From the outcomes of such an analysis (for an example see table 3), all the other steps can be performed.

Fig. 2: Suggested methodology for defining the RFId-based data gathering sub-system

14


The third concerns the definition of the operational procedures according to which the RFId-based data gathering sub-system must be used and of the databases the use of the sub-system allows for being recorded (for an example see tables 1 and 2). The fourth step, which must be performed once the use mode of the RFId-based data gathering sub-system is defined, refers to the selection of the cases for the RFId transponders, i.e. it refers to how fasten transponders to materials. In making such a selection great importance should be given to the types and shapes of the materials and to the frequency according to which transponders must be fasten to and unfasten from the corresponding material. Finally, the fifth step concerns the choice of the radio frequency characterizing the RFId-based data gathering subsystem. Also such a choice depends on the analysis performed in step 2 and, in particular, on the material types, which characterize the context where the sub-system must be implemented. Future developments of the present work will be the definition of the data gathering sub-systems for the engineering and purchasing processes, and the application of the same system to the suppliers of the studied company.

References Bertrand, J.W.M., Muntslag, D.R. (1993).Production control in engineer-to- order firms. International Journal of Production Economics 30/31, 3–22. Caridi, M., Crippa, L., Perego, A., Sianesi, A., Tumino, A., (2009) Do virtuality and complexity affect supply chain visibility?; International Journal of Production Economics (article in press) Caron,F., Fiore, A. (1995). Engineer to order’ companies: how to integrate manufacturing and innovative processes. International Journal of Project Management, 13 (5), 313-319. Chopra, S., Meindl, P., 2001. Supply chain management. Strategy, planning and operation. Prenctice Hall, Upper Saddle River, New Jersey. Closs, D.J., Goldsby, T.J., Clinton, S.R. (1997). Information technology influences on world class logistics capability. International Journal of Physical Distribution and Logistics Management 27 (1), 4–17. Forrester, J.W., 1961. Industrial Dynamics. Pegasus Communications, Waltham, Massachussets. Gosling, J., Naim, M., (2009) Engineer-to-order supply chain management: A literature review and research agenda.International Journal of Production Economics, 122 (2), 741-754. Gustin, C.M., Daugherty, P.J., Stank, T.P., (1995). The effects of information availability on logistics integration. Journal of Business Logistics 16 (1), 1–21. Hicks, C. McGovern, T., Earl, C. F. (2000). Supply chain management: A strategic issue in engineer to order manufacturing International Journal of Production Economics, 65 (2), 179-190 Kaipia, R., Hartiala, H., (2006). Information-sharing in supply chains: five proposals on how to proceed. The International Journal of Logistics Management 17 (3), 377–393. Little, D., Rollins, R., Peck, M., Porter, J.K., 2000. Integrated planning and scheduling in the engineer-to-order sector. International Journal of Computer Integrated Manufacturing 13, 545– 554. M. Karkkainen, J. Holmstrom, K. Framling and K. Artto, (2003) Intelligent products—a step towards a more effective project delivery chain, Computers in Industry 50 (2), 141–151. Mohr, J., Sohi, R.S., (1995). Communication flows in distribution channels: impact on assessments of communication quality and satisfaction. Journal of Retailing 71 (4), 393–416.

15

Tommaso Rossi and Margherita Pero Sterman J., 2000. Business dynamics: systems thinking and modeling for a complex world. McGraw Hill, Homewood, Illinois. Swaminathan, J.M., Tayur, S.R.(2003). Models for supply chains in EBusiness. Management Science 49 (10), 1387–1406.

16

A Structural Analysis of Information Technology (IT) Integration in Food Supply Chains and Firm Innovativeness

Suhana Mohezar and Claudine Soosay

Abstract The Malaysian food industry is undergoing a rapid transformation in response to the evolving consumer demands and intensifying competition. Firms in this sector are increasingly developing their innovative capabilities by integrating their Information Technology (IT) with supply chain members in order to sustain their competitive advantage. This study develops a framework which captures the impact of the technology integration on firms’ innovativeness, more specifically the level of product, process and relational innovation. This framework was empirically tested using cross-sectional data collected from both upstream and downstream perspectives of firms positioned at different nodes in the supply chain. Based on structural equation modelling, the findings demonstrate that the implementation of IT integration has a significant impact on firms’ relational innovation performance, while its effect on process innovation is only marginal. Product innovation however, is not associated with IT integration.

Keywords: Information Technology, Supply Chains, Food Industry, Innovation Performance

1 Introduction Organisations in the food industry constantly face various challenges such as increasing globalisation, highly differentiated and segmented food markets; as well as stringent regulations encompassing food safety, quality assurance and environmental standards. In response to such challenges, firms are gradually building up their innovative capacity as a means to achieve sustainable competitive advantage. Over the past few decades, the emphasis has been on supply chain integration using information technology (IT) as a strategic initiative, where firms could develop innovative capabilities in various areas, such as new product development, process improvement, service delivery, capacity planning and market expansion (Kark17


kainens 2003; Kelepouris et al. 2007). Although empirical studies support IT as an enabler of innovation, these are predominantly tested and highlighted using developed economies (Li 2005; Wu et al. 2006). Theories developed in a setting of mature markets need to be re-examined in the context of developing nations, as they may react differently due to the varying economic, cultural and regulatory settings (Austin 1990). This study extends this perspective and investigates the practicality of supply chains, using Malaysia as an example of a developing nation. Malaysia is one of the most affluent developing nations in Asia, with a rapidly growing food industry estimated at US$20 billion and aims to be the international ‘Halal’ food hub valued at US$150 billion annually (Malaysian Industrial Development Authority 2009). Although this sector provides enormous opportunities, skills shortages and lack of technology are evident factors preventing substantial development in this industry. In order to further develop this sector, the Malaysian Government has identified the food industry as an engine of growth (under the Ninth Malaysia Plan and Third Industrial Masterplan) and the need to improve the information technology infrastructure in its relevant supply chain operations (Malaysian Ministry of International Trade and Industry 2006). This paper provides perspectives on the relationship between IT integration in supply chain operations and firms’ innovativeness in the food industry. For the purpose of this study, IT integration refers to the adoption of supply chain technologies, supporting business processes and electronic transactions between firms and their immediate suppliers and customers. In order to better understand this issue, we developed a conceptual model explaining the impact of the technology integration on relational, product and process innovation at the firm-level. In order to validate the conceptual model, we collected cross-sectional data from Malaysian firms involved in food supply chains and employed Structural Equation Modelling (SEM) to determine the relationships established. The findings of the study provide a platform and opportunities for more effective managerial decision making, as well as strategic development and allocation of resources in the food industry. Additionally, this study also informs the government’s business support service strategy on the economic and commercial viability of Malaysian manufacturing activities and food products.

2 Literature Review 2.1 Innovation in the Food Industry The positive impact of firms’ innovativeness and organisational performance is well established in the literature (Hult et al. 2004; Porter 1980; Schumpeter 1949). Innovativeness refers to a firm’s capacity to engage in innovation (Wang and Ahmed 2004). Various definitions of innovation appear in the literature. For instance, Betz (1998) defines innovation as an introduction of a new or improved product, process or service into the marketplace, while Damanpour (1991) assumes innova18

A Structural Analysis of IT Integration in Food Supply Chains and Firm Innovativeness

tion as the generation, development and adaptation of novel ideas on the part of the firm. Other authors (Afuah 2003; Schumpeter 1949) contend that the concept of innovation not only relates to any new ideas or practices which are new to firms, but should also provide significant value to the adopting organisations as well as customers. Therefore, we conclude that innovation refers to the generation, acceptance and implementation of new ideas, processes, products or services, which provide improvement to the adopting organisation as well as customers. For the customers, the value is reflected in lower cost products or services with improved attributes, while for firms the value is indicated by higher returns, increased market shares, new customers or markets (Schumpeter 1949). In the food industry, innovation serves as an important source of competitive advantage for organisations. Recent socio-economic developments have resulted in a change in performance requirements for food supply chains, forcing firms to enhance innovativeness; not just in developing new products, but in all aspects of business. Increasing consumer awareness and demands for improved food products, particularly fresh produce, drives food businesses to invest in processing and logistics technologies that could maintain the quality of the product (Mangina and Vlachos 2005; Van Der Vorst et al. 2005). Further, food due to its high perishability requires not only time-efficient supply chains but also continuous monitoring. For instance, the success of prepared salads in the UK, as compared in the US, is largely attributed to the efficiency in logistic operations (Fearne and Hughes 1999). In the UK, prepared salads will be in retail stores within two days and consumed within five days of harvest, which is half of the time the products spend in transportation in the US. The establishment of more stringent regulations concerning the food safety is also seen as an accelerator for firms to innovate. The European Union Council of Ministers has introduced the “General Food Law”, which places responsibilities on producers, manufacturers, caterers and other food operators in the supply chain to ensure food safety (Opara 2003). This obligation demands firms seek more information on the upstream production practices, creating a need for them to invest in modern tracking methods that could improve the product traceability. These changes and developments in the food industry, as well as the nature of the product characteristics, have clearly indicated an essential need for firms to improve their organisational innovation capabilities. The advancement of information technologies in managing the supply chain and logistics operations is seen as a catalyst for firms to build their innovative capacity. By exploiting the technologies, they would be able to optimise their production and distribution process, reduce their operational costs, develop good relationships with trading partners, improve the quality of products produced and satisfy the diversifying customers’ demands. Examples of such technologies include Electronic Data Interchange (EDI), data loggers, Reefer Gensets, Radio Frequency Identification (RFID) and Vendor Managed Inventory (VMI) Systems. 19


3 Theoretical framework and hypotheses development In this study, the impact of IT integration on the firms’ innovativeness was examined in terms of relational, process and product innovation. The relationships between IT integration and these three innovation dimensions are discussed as follows: Relational innovation refers to the ability of firms to expand into new markets, strengthen the business networks and improve their relationships with suppliers and customers (Lefebvre et al. 2003). Various studies of IT integration suggest the significance of IT integration on the firm’s relational innovation (Iacavou et al. 1995; Wilson and Vlosky 1998). The technology offers a new communication medium and creates an opportunity for firms to establish interactive relationships with supply chain partners through information sharing. For instance, the deployment of eprocurement systems enables firms to exchange operational data such as level of inventory, new order, payment status, invoice and transportation schedule (Angeles and Nath 2007). Other supply chain technologies such as an electronic marketplace, provide firms opportunities to identify suppliers or customers, compare prices, terms and negotiations, as well as conduct basic commerce transactions online (Eng 2004; White et al. 2007). This technology allows companies to expand globally and enter new markets that were previously limited due to geographical barriers. It is apparent therefore, that IT could serve as an important enabler for the relational innovation at the firm level. Based on this argument, this study posits that: H1. IT integration is positively related to a firm’s relational innovation performance. Process innovation is typically introduced to improve operational efficiency, flexibility, responsiveness, production, distribution activities and reduce costs (Jusoh and Parnell 2008; Prajago et al. 2007). There is substantial empirical evidence to support the importance of technology integration in process innovation (Hill and Scudder 2002; Kelepouris et al. 2007). The adoption of IT integration in supply chain operations has the potential to enhance the speed, quality and quantity of information exchanged (Wu et al. 2006). Timely and accurate information flows enable firms to reduce uncertainties and improve operational efficiencies. For example, the use of vendor-managed inventory (VMI) systems grant suppliers access to their customers’ real-time inventory data and replenish stock on a proactive basis (Disney and Towill 2003). By allowing firms to access the real-time data rather than forecast data, buffer inventories can be removed, resulting in reduced inventory costs. Organisational investment in IT devices such as RFID, which can facilitate in product tracking, offer firms great opportunities for the efficient traceability process in the supply chain from harvest through transport, storage, processing, distribution and sales at significantly reduced labour costs (Attaran 2007; Opara 2003). The automated-capture of traceability information can assist firms to address the general public’s concerns on the rising incidence of food-related illness. Drawing upon this literature, this study therefore hypothesises that: 20

A Structural Analysis of IT Integration in Food Supply Chains and Firm Innovativeness

H2. IT integration is positively related to a firm’s process innovation performance. Product innovation can be referred to as the introduction of new goods or services into the market and enhancing the quality of existing products (Jusoh and Parnell 2008; Prajago et al. 2007). Some studies demonstrate that IT integration has a positive effect on a firm’s product innovation performance (Dobbs et al. 2002; Fearne and Hughes 1999). The integration of bar-coding, electronic-point-of-sales (EPOS) and data warehousing technologies allows firms to gather and manipulate information for developing knowledge about consumers’ purchasing behaviours. This ability has ultimately enabled firms to engage in new product development that could satisfy the diversified customers’ demands. In addition, the implementation of a supply chain technology - Time-Temperature Integrator (TTI) can result in an improved quality of food products. The technology provides firms the ability to monitor the temperature of perishable food at each stage of the supply chain and reveal any abusive storage conditions that may affect the product attributes (Sahin et al. 2007). Following this trait, this study asserts that: H3. IT integration is positively related to a firm’s product innovation performance. Following the extant literature, a research framework was developed. The framework posits that IT integration has a positive influence on organisational innovativeness comprising product, process and relational innovation (Figure 1).

Relational Innovation

H1

IT Integration

H2

Process Innovation H3

Product Innovation Fig. 1: Conceptual Model for IT Integration and Organisational Innovation Performance

21


4 Research Methodology 4.1 Operationalisation of Constructs The constructs used in this study are established measures from the literature which were adapted to the context of this study. The independent variable – IT integration, was measured using two items adapted from Zhang and Dhaliwal (2008) and Ranganathan et al. (2004). Respondents were asked to indicate the percentage of transactions conducted electronically with suppliers and customers. Based on Moore (1998), Lefebvre et al. (2003) and Aramyan et al. (2007), nine items were adopted to measure the level of a firm’s relational, product and process innovation performance. These items assess the extent to which the IT integration has increased a firm’s capability to produce a variety of new products, improve the quality of food produced, enhance the logistics and distribution process and improve the relationships with suppliers and customers. Respondents were asked to rate their perceptions on the level of their firm’s innovative capabilities in relation to IT integration on a 7-point Likert scale, ranging from 1(strongly disagree) to 7(strongly agree).

4.2 Survey Administration and Sample This study employed a survey method, using a questionnaire, to test the conceptual model and hypotheses developed. The questionnaire was pilot-tested with a sample of twenty-seven organisations in the food industry. Feedback from the pilot test was used to refine the questions for the larger study. The sampling frame for this study was drawn from the list of companies involved in the Malaysian food industry registered with Malaysian External Trade Division Corporation (MATRADE) as of February 2009. They included input suppliers, agricultural producers, food manufacturers, wholesalers, import and export agents, distributors and retailers. In order to avoid a case in which some members of the population were significantly under or over represented by the sample, this study utilised a stratified random sampling (Hussey and Hussey 1997), which was made based on the size and organisations’ position in supply chains. Only firms that have adopted supply chain technologies (i.e. ERP, EDI) were included in the sampling frame. A questionnaire, including a cover letter, self addressed and stamped envelopes was mailed to the CEO, managers or owners responsible for IT-related decision making in the firm. Of 1200 questionnaires mailed out, 253 questionnaires were returned, which resulted in a 21 per cent response rate. Table 1 presents the sample characteristics. The results reflect a fair distribution of sample across sizes and sectors.

22

A Structural Analysis of IT Integration in Food Supply Chains and Firm Innovativeness Frequency

Percentage (%)

Input supplier

30

11.8

Agri-producer

34

13.4

Packaging supplier

37

14.6

Manufacturer

42

16.5

Wholesaler/agent/importer/exporter

41

16.1

Logistics and transportation

30

11.8

Retailers

39

15.4

Total

253

100

less than 250 thousand

39

15.4

250 thousand-1 million

53

20.9

1 million-10 million

63

24.8

10 million-25 million

53

20.9

more than 25 million

45

17.7

Total

253

100

Position in the chain

Annual sales revenue (in Ringgit Malaysia)

Tab. 1: Profile of Respondents

5 Analysis and Findings This study employed structural equation modelling (SEM), with a two-stage model estimation, as recommended by Anderson and Gerbing (1988). In this approach, a confirmatory factor analysis (CFA) was first conducted, followed by a structural model analysis. By employing this approach, the source of poor model-fit can be identified easily (Kline 1998). The model fit was evaluated based on multiple fit indices, which include p-value for chi-square index, Goodness-of-Fit Index (GFI), Standardised Root Mean Square (SRMR), Root Mean Square Error of Approximation (RMSEA), Tucker-Lewis Index (TLI) and Comparative Fit Index (CFI) (Bollen and Long 1993; Schumacker and Lomax 2004). Iterative modifications were made to improve the model-fit statistics by observing the standardised residual covariance matrix, modification indices, sample correlations and regression coefficients (Byrne 2001). Only one item was altered at a time to avoid overmodification of the model (Joreskog and Sorbom 1989).

23

Suhana Mohezar and Claudine Soosay Factors and Items

CFA (N=253) SFL

t-value

SMC

Improved supplier and customer relationships

.92

a

.84

Increased market share

.87

21.60*

.76

Improved customer satisfaction

.93

26.07*

.87

Improved ability to retain partners, customers and suppliers

.86

20.74*

.74

Relational innovation (α=.94)

Process innovation (α=.70) Improved food traceability and monitoring

.56

a

.31

Improved distribution and production responsiveness

.50

10.66*

.25

Improved storage and transport conditions that are optimal for good quality product

.67

11.26*

.45

Product innovation (α=.65) Improved ability to produce variety of products

.56

a

.31

Improved ability to produce good quality products

.97

20.56*

.95

IT integration (α=.87) Percentage of online transactions conducted with immediate suppliers

.97

a

.96

Percentage of online transactions conducted with immediate customers

.79

17.88*

.62

Composite Reliability

AVE

.80

.58

.75

.50

.67

.50

.67

.50

²=70.49, p 20

19.1

0 -5

21.7

6 – 10

34.8

11 – 5

24.4

16 – 20

13.9

> 20

5.2

Less than $500K

13.3

$500K - $ 1M

23.8

$1M - $ 10M

21.0

$11M - $50M

15.2

$51M - $100M

12.4

More than $100M

14.3

Less than 100

53.3

100 – 499

31.5

500 – 999

9.6

More than 1000

4.4

Ownership

Years of experience in logistics industry

Years operated in China

Total revenue last year (US$)

Number of employee in China

Note: * Percentages in this categories do not sum to 100. Respondents were asked to indicate all items that applied to their operations.

Tab. 1: Profile of responding LSPs

89

Ming J. Ding and Booi H. Kam

Item

Factor 1 (BPP)

Customer service performance benchmarking

0.892

Operational performance benchmarking

0.839

Performance measurement metrics

0.811

Functional cost performance benchmarking

0.804

Customer feedback and complaint handling

0.748

Upgraded application for computer system

0.618

Factor 2 (PIR)

Triggered operation schedules

0.809

Door-to-door delivery services

0.714

Flexible scheduling solutions

0.705

On-time delivery procedures

0.66

Processes to changing customer requirement

0.596

Factor 3 (ILS)

Operational information sharing with partners

0.838

Operational information shared between departments

0.759

High integrated functional services

0.643

Eigenvalues

6.436

1.584

1.183

Percentages variance

45.973

11.311

8.452

Accumulated variance

45.973

57.284

65.736

Cronbach's α

0.916

0.815

0.718

Note: The EFA used principal components analysis with VARIMAX rotation. The initial factor solution on the 24 items resulted in five factors with eignvalues greater than unity. To purify the list, items with loadings of less than 0.50 on all factors or items cross-loaded on more than one factor were removed (Hair et al. (2006). This table shows a purified list of 14 items with a clear factor structure showing three factors. The 10 items deleted were: 1. Time-based logistics solution. 2. Shorter or smaller size shipments. 3. Express delivery services. 4. Procedures to reduce damage, thefts and tampering during transportation and storage. 5. Roles and responsibilities in the supply chains involved. 6. Integrated information systems. 7. Electronic Data Interchange (EDI) services. 8. Usage of formal planning systems. 9. Effective quality assurance program. 10. Regularly review of customer services Factor loadings < 0.5 have been supressed.

Tab. 2: Factor analysis of items representing Business Processes and Standard Operation Procedrues of LSPs in China

90

Business Processes and Logistics Service Competencies of Logistics Service Providers in China

Items

Factor 1 (LPC)

Innovative supply chain solutions

0.846

Information system compatibility

0.786

Widespread or extensive distribution coverage

0.783

Cost effective transport and distribution network

0.783

Secured information systems

0.773

Value-added logistics services

0.743

Integrated customer services

0.726

Global distribution coverage

0.702

Pre-planned customer services

0.628

Logistics industrial expertise

0.501

Factor 2 (ASCS)

Expedited delivery services

0.899

Rapid response to customer needs

0.861

Flexible delivery schedule

0.792

Short delivery lead times

0.748

Eigenvalues

8.804

8.286


62.889

8.826


62.889

71.175

Cronbach's α

0.921

0.923

Note: The EFA used principal components analysis with VARIMAX rotation. Factor loadings < 0.5 have been supressed.

Tab. 3: Factor analysis of items representing L&SC competencies of LSPs in China

4 Results 4.1 Logistics positioning competencies (LPC) Models 1 to 3 in Table 5 show the influence of different factors on a LSP’s LPC in China. In Model 1, with only the two control variables in the regression equation, GC shows a statistically significant effect on LPC, while CS does not. As a baseline model explaining less than 5% of the variance, this finding suggests that in the absence of BP&SOP variables, the geographical reach of LSPs would have a marginal effect on their LCPs. As the three BP&SOP variables enter the regression equation in Model 2, the effect of GC fades into obscurity. PBP and PIR both have a statistically significant effect on LPC. ILS, however, does not. What is noteworthy is that the percent of variance explained jumps from less than 5% in Model 1 to almost 39% in Model 2, suggesting that processes put in place to benchmark performance against others in the industry and those established to increase customer responsiveness are vital in building a LSP’s LPC. In Model 3, which tests the effect of FTW on the relationship between the three BP&SOP variables on LPC, the dominance of PIR remains statistically significant, 91


but that of PBP becomes insignificant. Instead, the effect of ILS begins to show, though the sign of the regression coefficient is not positive as expected. However, the interaction effect of FTW and ILS does have a positive influence on LPC. Items

Factor 1 (FTW)

Warehouses for handling perishable goods

0.839

Advanced machinery for loading and unloading

0.775

Modernized warehousing systems

0.775

Secured packing methods

0.752

Advanced packing facilities

0.741

Adequate warehouse facilities

0.732

Upgraded warehouse computer systems

0.713

Fully owned transpiration fleet

0.696

Upgraded transport facilities

0.693

Reliable secured warehouse systems for high value goods

0.682

Computer systems for bar-coding or inventory counting

0.582

Factor 2 (ICT)

Advanced computerized documentation systems

0.843

State-of -the-art software for forecasting and scheduling

0.843

Investment on computer hardware and software

0.587

Factor 3 (DN)

Distribution network in the China western remote areas

0.844

Nation-wide distribution network

0.809

Eigenvalues

8.691

1.507

1.141


54.322

9.416

7.128


54.322

63.738

70.866

Cronbach's α

0.943

0.804

0.832

Note: The EFA used principal components analysis with VARIMAX rotation. The initial factor solution on the 21 items resulted in 3 factors with eignvalues greater than unity. To purify the list, items with loadings of less than 0.50 on all factors or items cross-loaded on more than one factor were removed (Hair et al. (2006). This table shows a purified list of 16 items with a clear factor structure showing three factors. The 5 items deleted were: warehouse function outsourced; warehousing systems for handling hazardous and flammable goods; transportation function outsourced ; on-line real-time track and trace function; and multimodal services. Factor loadings < 0.5 have been supressed.

Tab. 4: Factor analysis of items representing physical assets and informatin resources of LSPs in China

92

Business Processes and Logistics Service Competencies of Logistics Service Providers in China Dependent Variable: LPC Model 1

Model 2

Dependent Variable: ASCS Model 3

Model 4

Model 5

Model 6

CS

-0.01

-0.015

-0.003

-0.199*

-0.193**

-0.159**

GC

0.259*

0.148

0.075

0.231**

0.102

0.028

PBP

0.232**

0.101

0.199**

-0.314

PIR

0.39***

0.664***

0.513***

0.811***

ILS

0.075

-0.56*

-0.009

-0.216

FTW x PBP

0.005

0.859

FTW x PIR

-0.626

-0.736*

FTW x ILS

1.167**

0.374

R2

0.065

0.415

0.518

0.047

0.447

0.506

Adjusted R2

0.048

0.389

0.483

0.031

0.422

0.470

F

3.944**

15.774***

14.536***

2.835

17.971***

13.839***

N

117

117

117

117

117

117

Notes: Figures shown are standardized coefficients (i.e., beta values) *p < 0.10; **p < 0.05; ***p < 0.01

Tab. 5: Hierachical regression results

These findings suggest that processes established to facilitate the provision of integrated logistics services may have a counter-productive effect on LPC, due, perhaps, to the fallouts of information integration (i.e., the sharing of information with partners may have disadvantaged the LSPs), unless such integration is backed up by having ready access to, or ownership of, appropriate supporting logistics infrastructure. In other words, unless LSPs have the support of a substantial logistics infrastructure base, sharing of information with partners could dampen their competitve edge, as partners with better means of utilizing the information available could sieze the oportunity to excel.

4.2 Agile supply chain solutions (ASCS) The influence of different factors on a LSP’s ASCS is shown in Models 4 to 6 in Table 5. Model 4, the baseline model, indicates that both CS and GC do have a statistically significant effect on ASCS, with CS having a negative but GC a positive impact on ASCS. This baseline model only manages to explain about 3% of the variance. Again, this finding suggests that, in the absence of BP&SOP variables, the geographical reach of LSPs would have a minor effect on their ASCS; but company size, as expected, would have a dampening effect. With the inclusion of the BP&SOP variables, the effect of GC wanes but that of CS remains with a negative sign. Of the three BP&SOP variables, PBP and PIR show statistically significant effect on ASCS, while ILS does not, reflecting, once again, the importance of having processes to both benchmark performance and to increase customer responsiveness in nurturing ASCS. 93


The moderating effect of FTW on the relationship between the BP&SOP variables and ASCS shown in Model 6 indicates that the interacting effect of FTW and PIR is statistically significant, but not those of FTW and PBP, and FTW and ILS. The sign of the regression coefficient of FTW and PIR, however, is negative, which is contrary to expectation. The main effect of PIR on ASCS persists, while the negative effect of CS also shows no sign of abating. We suspect a trade-off effect between having processes in place to increase customer responsiveness and having ready access to transport and warehousing faciities. As access to transport and warehousing faciities increases, it creates a constraint on the staging of customer responsiveness processes, to the extent that it could reduce the effectiveness of such processes in nurturing ASCS.

5 Discussion and conclusion The results of EFA analysis suggest that LPC competencies and ASCS are two key factors for LSPs to achieve competitive advantage in the Chineses logistics market. LPC, which include providing customers with innovative supply chain solutions, compatiable or secured information systems, extensitive distribution channels, cost effective transport and distribution networks, and logistics industrial expertise, offers a mix of building blocks for LSPs to create customer-centric differentiation strategies in the complex Chinese logistics market to gain competitive advantage. This is consistent with Wang et al.‘s (2006) observation that many LSPs in China have abandoned cost leadership to pursue differentiation strategy to cope with the intense competition in the Chinese logistics markets. Likewise ASCS, which encompassess expedited delivery servcies, rapid response to customer needs, flexible delivery schedule, and short delivery lead times, are also competitive advantage enablers for LSPs in China (Stank & Lackey 1997). The results of the hierachical multiple regression analysis reveal three major findings. First, they show that PBP and PIR are two significant factors for LSPs to compete in the Chinese logistics market. ILS, however, was not identified as a signficant variable. These results add weight to the argument that private-owned LSPs in China find it hard to provide customers with integrated logistics services, due to their limited resources (Duan 2006). Second, the regression results also show that company size is a statistically significant negative predictor of ASCS. It suggests that the larger the size of the LSP, the harder it becomes for the firm to provide customers with agile supply chain solutions. This finding reflects the situation experienced by some asset-heavy stateowned LSPs with large scale operations: they face overstaffing problems and lack customer orientation. Small private-owned LSPs, on the other hand, have been able to offer customers agile supply chain solutions. Third, FTW, as a moderator, is a two-edged sword. While it bolsters the processes put in place to support integrated logistics services to enable LSPs to nurture their 94

Business Processes and Logistics Service Competencies of Logistics Service Providers in China

LPC, FTW could also dampen the effectiveness of processes designed to increase customer responsiveness to offer ASCS, This finding lead us to conclude that the moderating effect of FTW is not linear in the context of the Chinese logistics market. We attribute this unexpected finding to the presence of the asset-heavy stateowned companies, which are less capable of responding flexibly to customer needs. We conclude that in the context of the Chinese logistics market, being large and asset heavy need not necessarily accord LSPs a competitve edge. Having customer responsive processes and procedures for benchmarking performance are good operational practices which could help LSPs to acquire two vital service competencies to gain competitive advantage.

6 Suggestions for further research The study draws theoretical foundations from the RBT and relevant logistics literature to explore key factors influencing L&SC competencies of LSPs in China and how BP&SOPs contribute to operational capabilties and L&SC competencies. This research has focused only on the intangible resource of business processes. The effects of other resources, such as relationship management and social capital, have not been fully explored. Future research on LSPs‘ operational competencies may consider exploring the effects of other intangible resources on L&SC capabilities and competencies.

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Managing Production Ramp-ups in the European Automotive Supply Chain – The Supplier´s View

Tobias Held

Abstract Shrinking product life cycles, faster innovation cycles and the growing amount of highly complex new product introductions are leading to a high importance of production ramp-up management. While a lot of in-depth analysis has been done covering production ramp-ups at original equipment manufacturers (OEMs) in the automotive industry, suppliers have not been analysed empirically in such detail. This article presents some major results of an explorative survey conducted in 2009 covering 52 European automotive suppliers.

Keywords: Ramp-up management, automotive supply chain

1 Introduction - a concise overview of ramp-up management A dynamic economic development, saturated markets and high competitive demands are trends, which all companies in the automotive industry have to face (cp. e.g. Ihme 2006; Giesen & Hillbrand 2006, p. 168; Wagner 2006). The financial and economic crises have lead to a further intensification of competitive pressure (Fockenbrock 2009; Steiger 2009; Anonymous 2010). To ensure market survival many OEMs have put a focus on quicker innovation cycles and faster new product development (Juerging & Milling 2006, p. 3). As a consequence not only are car generations being replaced more frequently but also the substitution of components and single parts is occurring more often. In addition, more efficient supply chain management with increased outsourcing percentages has been one important goal of nearly all car manufacturers. In this regard suppliers on all levels have become more and more important in the last decades (Accenture 2001; Alicke, Graf & Putzlocher 2004; Kurek 2004): Approx. 60-75 % of the value added is created by the different groups of suppliers in the European automotive industry (Mercer Management Consulting et al. 2004; Graf 2006; Palm & Sihn 2007). In the course of the rationalization of pre-production and final assembly activities not only have simple parts and components been outsourced to suppliers but also modules and whole systems (Clark & Futjimoto 1991; 99

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Vahrenkamp 2007, p. 353; Boston Consulting Group 2004). These are not only produced by suppliers – sometimes on the spot or close to final assembly sites – a further huge amount of development work (party even basic research) is done by these module and system suppliers (Novak & Eppinger 2001; Lamming 1993; SM&P 1993). As a result suppliers play an important role in the development and production processes of automotive supply chains: “The customer depends on the supplier`s know-how and relies on the supplier to deliver on time and on target. Committed ever more heavily to the customer, the supplier depends on it for its future revenue stream. The two sink or swim together.” (Kamath & Liker 1994, p. 165). To achieve competitive advantages in their highly competitive markets automotive suppliers are striving to accelerate their innovation processes1 to facilitate reduced time to market and time to volume. As a consequence the number of production ramp-ups is increasing considerably and the importance of managing them effectively and efficiently is becoming one of the most important tasks that has to be focused on (Rädle 2005, p. 83; Risse 2002; Peters & Hofstetter 2008). Suppliers at different levels (tiers) have to concentrate on improving the coordination and controlling of ramp-up activities from the first prototypes until mass production has been stabilized (Romberg & Haas 2005, p. 24). They have to optimize their internal processes permanently as well as their interfaces with other suppliers and their customers (Druml & Blechinger 2008; Vahrenkamp 2007). The required logistics and organizational processes still have high potential for improvements and costsavings (Hüntelmann, Reinsch & Märtens 2007). Fig. 1 presents the results of the survey conducted (cp. chapter 3) concerning the overall importance of ramp-up management at European automotive suppliers and two significant drivers that were analyzed: Using a dedicated ramp-up management was rated unconditionally necessary by 49 from the 52 companies in the survey. Some exemplary reasons and advantages that were explicitly mentioned by the experts in an open-ended question were: “continuous progress monitoring”, “early identification of risks and potentials”, “fundamental quality improvements and a goal-oriented cooperation with further suppliers”.

___________________ 1

The speed of R&D is currently an important problem in the automotive industry: 56% of automotive companies rate themselves as below average or poor in this regard (Boston Consulting Group 2009).

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Managing Production Ramp-ups in the European Automotive Supply Chain - The Supplier’s View Did you experience a reduction in the product-life-cycle length?

Did the number your of product variants increase? Constant 94.2%

No 30.8%

... 69,2% 5.8%

Yes

Increased Do you think there are alternatives to using a dedicated ramp-up management? Yes 3.8%

96,2% No

n=52; t=09/2009

Fig. 1: Importance of ramp-up management at European automotive suppliers

2 Introduction to production ramp-ups in the automotive supply chain The time and cost sensitive ramp-up phase has a significant impact on both productivity and product yield and hence on the success of the entire company (Bischoff 2007; Straube & Fitzek 2005; Almgren 1999a). However there is no overall accepted definition of the ramp-up phase and ramp-up management (Schuh, Desoi & Tücks 2005, p. 258; Wildemann 2008; Pfohl & Gareis 2000). The production ramp-up phase can be considered as an interface between design and mass production (Risse 2002; von Wangenheim 1998; cp. fig. 2 based on Scholz-Reiter et al. 2007; Näser 2007). To master ramp-up activities is daily business in many companies – nevertheless several companies have neglected the optimization potentials in this field in the last decades (Kuhn et al. 2002) and many do not use adequate methodical support and / or do not apply appropriate standards (Hüntelmann, Reinsch 101

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& Märtens 2007, p. 116). As a result, in contrast to the matured concepts, methods and theories for production planning and control for serial production, there is still enormous potential for improvement in the management of ramp-ups (Bischoff 2007; Ciambrone 2008). Therefore, a lot of research covering the design of rampup processes has been done – especially in the past few years – mainly focussing on the final assemblers in the automotive industry (cp. e.g. Audi: Beetz, Grimm & Eickmeyer 2008; Volvo: Almgren 1999b; Daimler trucks: Lehmann & Grzegorski 2008; Mercedes: Schick & Binder 1998; VW: Martens 2008).2 The issues of integrating suppliers during production ramp-ups at OEMs has also become a research topic in the recent years (cp. e.g. Denzler 2007; Gehr 2007; Kist 2008; Witt 2006). Product creation processes

Production processes

Launch and change-over phase (“ramp-up“)

Prototyping

Pilot series “Pre-“ series

“Null“ series

Production start-up Serial production

Stage Gates Release of technical drawings

Start launch phase

Start production tests

Start of production (SOP)

Reaching of full production capacity

Fig 2: Ramp-up phases of OEMs in the automotive industry (highly simplified)

The automotive supply chain is very complex, and several participants are involved (cp. fig. 3; based on Fawcett, Ellram & Ogden 2007). This paper focuses solely on the supplier’s point of view. There are several possibilities to differentiate suppliers: E.g. Kamath & Liker (1994) distinguish between “partner” (full-service provider), “mature” (full-system-provider), “child” and “contractual” supplier roles. Based on the design responsibilities Scholz-Reiter et al. (2007) differentiate suppliers of components/parts, systems and modules. Twigg (1998) goes as far as to pro-

___________________ 2

Concerning other industries compare Fjallström et al. 2009 (outdoor products); Held 2009 (fast moving consumer goods); Terwiesch, Chea & Bohn 1999 (hard disk drives); Pufall, Fransoo & Kok (mobile phones). General ramp-up issues have already been discussed for some time cp. Clawson 1985 and Sounder & Padmanabhan 1989. The first monograph discussing rampups at automotive OEMs was published as far back as the nineteen-fifties (Schieferer 1957).

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Managing Production Ramp-ups in the European Automotive Supply Chain - The Supplier’s View

vide eight different supplier types. This paper uses the supplier’s size measured by turn-over and tier judged by the companies themselves – as proposed by Liker et al. (1996). # Example Chrysler Customer

Customer

Distributor

Customer

Customer

OEM

Distributors 50,000

Service Provider

Production Facilities 40

System/module suppliers Supplier

Supplier

Supplier

Supplier

Supplier

Supplier

Supplier

Supplier

Supplier

Supplier

Customers 5,000,000

Distributor

Distributor

Service Provider

Customer

1st-Tier Suppliers 1,500

Supplier

Supplier

Supplier

This paper

Component suppliers Supplier

Supplier

Supplier

Supplier

2nd-Tier Suppliers 50,000

3rd…-Tier Suppliers 250,000

Part/material suppliers

Fig 3: The simplified automotive supply chain

3 The explorative survey conducted Based on literature research and an analysis of surveys already conducted at automotive OEMs a preliminary set of questions was complied. These questions were used for a pre-test and were discussed with some project managers who were responsible for production ramp-ups at two automotive suppliers. After refining the survey questions 183 companies from an online discussion forum for automotive ramp-up issues were selected. The contact people – picked from development, production or project management areas – were contacted online in the middle of August 2009 and were reminded once around the end of August 2009. Responses were included until 10th of September 2009. A return rate of 28.4% was achieved (52 companies). The first part of the survey covered some general questions concerning e.g. company size and position in the supply chain. To differentiate the companies for the analysis, different groups were established a) based on turn-over and b) based 103

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on position in the supply chain (cp. fig 4): All companies with less than €200m turn-over are classified as small and medium size companies (SME) in the following (unlike the European Commission 2006 definition because component, module and system suppliers in the automotive industry tend to be bigger companies).

€10m – €50m

SME < €200 m: 37.2%

< €10m

3.4%

2nd…nth Tier

9.6% €50m – €100m

26.9% 9.6%

11.5%

62.8%

€100m – €200m

73.1% > €200 m

n=52; t=09/2009

1st Tier

Fig. 4: Supplier groups: Suppliers clustered by turn-over / by tier

After providing a definition of ramp-up management the survey asked some questions concerning the perceived importance of ramp-up management, e.g. if dedicated ramp-up management approaches were implemented in one way or the other. The largest part of the survey focused on organizational, technical and employee issues (25 questions in total). In addition to asking closed questions (mainly using a 1 to 5 Likert scale) some open-ended questions were used. The former were analyzed and differentiated by size/tier basically using simple statistical methods; the latter by using text analysis. Some of the most important results are presented in the next chapter.

4 Key findings in the survey One part of the survey focused on organizational issues: 90.4% of the companies claimed that they practiced dedicated ramp-up management in one way or the other. The remaining companies that did not implement ramp-up management provided among other things the following reasons: “Ramp-up is fully managed by the customer (OEM)” and that “there was not enough man-power to take-over the additional tasks”. Those companies with a dedicated ramp-up management explicitly mentioned the use of organizational approaches such as assigning ramp-up managers, forming ramp-up teams and conducting short-term workshops. For example 24 of the companies (46.2%) implemented a ramp-up manager position (the percentage being 104


slightly higher for the 1st tier suppliers (51.4%); and considerably lower for the SME suppliers (25.0%)). A question asking about the methods and tools used to optimize ramp-ups, revealed that 69.2% of those suppliers analyzed use dedicated tools/methods – compare figure 5. Most methods used relate to project and risk management areas; those explicitly mentioned were – for instance – Six Sigma, sub-supplier evaluation sheets, Failure Mode and Effect Analysis (FMEA) and Advanced Product Quality Planning (APQP). These tools and approaches focus mainly on detecting and eliminating process deviations. Interestingly, the implementation of dedicated tools is strongly correlated with the size of the supplier but only very little with the position/tier in the supply chain: It seems that bigger suppliers use much more formalized methods and tools and OEMs do not force all their 1st-tier suppliers to use dedicated methods and/or tools. Do you use dedicated methods/tools to manage ramp-ups? Efficiency level monitoring

Six Sigma

eM-Plant Production trials Supplier days

SPICE Weak points analysis

Quality gate reviews

Heijuka

Value stream design

DOE CMMI Malfunction period analysis Value stream analysis

Handover checklists

Supplier evaluation 8D

Run status lists

No 30,8%

APQP

Yes 69,2%

Simultaneous Engineering

Design reviews LeanCheck

PPAP

FMEA

Safe Launch Concept

Kaizen Process analysis

Bottleneck analysis

Performance tests

PDCA

Stress simulations

Selection; Bold: mentioned by more than 10% of the companies; n=52; t=09/2009

Fig. 5: Methods / tools used during the management of production ramp-ups

Analyzing the answers concerning the level of satisfaction showed a variegated evaluation (cp. figure 6) – however, almost all the companies showed a high potential for improvement. For example, the transparency of the ramp-up status was 105

Tobias Held

evaluated sufficient by 51.9% of the companies (SMEs: 45.0%; bigger companies 56.3%).3 Only 36.5% evaluated the communication and controlling processes between the functional areas in their companies as sufficient (bigger companies with a slightly better evaluation than SMEs). Strongly agree

1.0

2.0

3.0

4.0

Bigger Companies SMEs

Strongly 5.0 disagree

n=52; t=09/2009

Fig. 6: Satisfaction concerning transparency, communication, change management and employees (averages)

Another part of the survey focused on staff issues. Only 34.6% of the companies in the survey argued that a sufficient number of employees was available to handle ramp-up problems. This seems to a big issue especially for SMEs: approximately three quarter of the companies with a turn-over below €200m claimed that more human resources would be required. The qualification level and the experience of the employees were rated sufficient by the majority of the companies in the survey (in particular true for SMEs). This might be one reason why most companies (53.9%) did not provide dedicated training (e.g. workshops) to improve production ramp-ups (this is particularly true for non 1st-tier suppliers) (cp. fig. 7).

___________________ 3

51.9% of the companies “agreed” or “strongly agreed” to the statement that their “transparency during production ramp-up was sufficient”.

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One big issue for the companies in the sample was dealing with changes4: Only 46.2% of the companies agreed with the statement that they have their change processes sufficiently under control. Do you use dedicated training programs to manage ramp-ups? All companies

No

53,8%

46,2%

Yes

n=52; t=09/2009

1st tier supplier

2nd tier supplier

26.7% No

45.9%

54.1%

Yes

Yes

No 73.3%

n=37; t=09/2009

n=15; t=09/2009

Fig. 7: Training implemented to improve the ramp-up phase Concerning the use of IT-technologies the survey revealed that although more than 70% of the companies use ERP systems to collect and analyze process data only about a third (32.7%) of the suppliers use dedicated IT-tools to manage their production ramp-ups. The only IT-tools mentioned very frequently were MicrosoftOffice-applications (especially MS-Project) and SAP-based solutions (notably used at bigger companies). An open question asking for ways to optimize production ramp-ups in the future showed that many companies are currently trying to optimize internal and external interfaces. Interestingly, it is the interfaces to further suppliers or subsuppliers in particular that are currently being reengineered at many companies (e.g. offering training and work-shops for sub-suppliers). Moreover, achieving more transparency by implementing standards (standard processes) seems to be the

___________________ 4

Customer specification changes are one of the biggest issues for automotive suppliers: According to Liker et al. (1996, p. 74) 46% of US suppliers experienced problems due to specifications changes of their customers, but only 23% of Japanese suppliers.

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focus of many of the companies analyzed at the moment. The bigger companies also seem to be working on optimizing ramp-ups at different global locations e.g. by implementing one central (lead) factory for process optimization and transferring the lessons-learned to other sites afterwards. One further aspect that seems to be increasingly important is managing several ramp-ups in parallel (“multi ramp-up project management”) – it seems as if it is not feasible to avoid realizing more than one ramp-up project at a time at many automotive suppliers (as most of them have several customers with diverse projects).

5 Conclusion and outlook The financial crisis, shorter product life-cycles, increasing complexity and the higher and higher differentiation create a high dynamic in the automotive industry. As a consequence not only OEMs but also suppliers on all levels have to face soaring ramp-up challenges. A dedicated management of ramp-up procedures is required to ensure a sound ramp-up and to optimize the processes of transferring development work into mass production from a theoretical point of view. This paper presented the results of an explorative survey conducted in Q3/2009 – which covered 52 responding European automotive suppliers: based on the results of the analysis it can be said that ramp-up management is of high importance to the vast majority of European automotive suppliers too and that a need exists to improve the management of their ramp-up projects. Regarding the challenges some supplier specific issues that seem nearly universally valid have been detected: the number of employees (especially experts) at most suppliers is more limited than at OEMs and suppliers sometimes have to face several ramp-up projects in parallel for different customers. As a result the day to day business does not always permit the same approaches used at car manufacturers. Nevertheless, dedicated ramp-up managers and ramp-up teams are implemented at nearly half of the suppliers and a huge number of the tools and methods is already in use at some companies. Currently, European automotive suppliers are mainly focussing on implementing/optimizing standard ramp-up processes, improving their interfaces with their sub-suppliers and establishing global ramp-up approaches. Future research might be valuable in a) duplicating the survey in other global regions, b) investigating the suppliers view on ramp-up management in other industries and c) using a larger number of responses to enable statistical significant hypothesis testing.

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Acknowledgement: I would like to thank all the industrial experts who have been willing to participate in the expert interviews and the survey conducted. Special thanks to Dip.-Ing. (FH) Yilmaz Yavuz for the support of the survey.

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Managing Production Ramp-ups in the European Automotive Supply Chain - The Supplier’s View Peters, N. & Hofstetter, J.-S. (2008): Konzepte und Erfolgsfaktoren für Anlaufstrategien in Netzwerken der Automobilindustrie, in: Schuh, G., Stölzle, W. & Straube, F. (ed.): Anlaufmanagement in der Automobilindustrie erfolgreich umsetzen, Berlin / Heidelberg, Springer, p. 9-30. Pfohl, H.-Chr. & Gareis, K. (2000): Die Rolle der Logistik in der Anlaufphase, in Zeitschrift für Betriebswirtschaft, 70. Jg. (2000), H. 11, p. 1189-1214. Pufall, A., Fransoo, J. C. & de Kok, A. G. (2007): What determines product ramp-up performance? A review of characteristics based on a case study at Nokia Mobile Phones, http://cms.ieis.tue.nl/Beta/Files/WorkingPapers/Beta_wp228.pdf, (last call-of 10.12.2009). Rädle, V. (2005): 5. Anlaufmanagement, in: Müller-Dauppert, B. (ed.): Logistik-Outsourcing: Ausschreibung: Vergabe: Controlling, München, Verlag Heinrich Vogel, p. 83-102. Risse, J. (2002): Time-to-Market-Management in der Automobilindustrie: Ein Gestaltungsrahmen für ein logistikorientiertes Anlaufmanagement, Berlin, Haupt Verlag. Romberg, A. & Haas, M. (2005): Der Anlaufmanager: Effizient arbeiten mit Führungssystem und Workflow: Von der Produktidee bis zur Serie, Stuttgart, LOG_X Verlag. Schick, M. & Binder, M. (1998): Sicherstellen der rechtzeitigen Teileverfügbarkeit durch Problemmanagement zum Serienanlauf – dargestellt am Beispiel der A-Klasse, in: Horvàth, P. & Fleig, G. (ed.): Integrationsmanagement für neue Produkte, Stuttgart, Schäffer Poeschel Verlag, p. 273-297. Schieferer, G. (1957): Die Vorplanung des Anlaufs einer Serienfertigung, Diss. Technische Hochschule Stuttgart, Stuttgart. Schneider, M. (2008): Logistikplanung in der Automobilindustrie: Konzeption eines Instruments zur Unterstützung der taktischen Logistikplanung vor „Start-of- Production“ im Rahmen der Digitalen Fabrik, Wiesbaden, Gabler Verlag. Scholz-Reiter, B., Krohne, F., Leng, B. & Höhns, H. (2007): Technical product change teams: an organizational concept for increasing the efficiency and effectiveness of technical product changes during ramp-up phases, in: International Journal of Production Research, Vol. 45, No. 7, 01. April 2007, p. 1631-1642. Schuh, G., Desoi, J.-C. & Tücks, G. (2005): Holistic Approach for Production Ramp-Up in Automotive Industry, in: Bramley, A., Brissaud, D., Coutellier, D. & McMahon, C. (ed.): Advances in Integrated Design and Manufacturing in Mechanical Engineering, Springer, p. 255-268. Souder, W. E. & Padmanabhan, V. (1989): Transfering new technologies from R&D to manufacturing, Research & Technology Management 32 (1989) 5 S. 38-43. SM&P (1993): Neue Perspektiven für eine effiziente Produktentwicklung, Bergisch Gladbach. Steiger, H. (2009): Innovationsfähigkeit ist wichtiger als Lohnkosten, in: VDI-Nachrichten 29.Mai.2009, p. 4. Straube, F. & Fitzek, D. (2005): Herausforderungen und Erfolgsfaktoren im Anlaufmanagement der Automobilindustrie, in: Jahrbuch der Logistik 2005, p. 44-47. Terwiesch, C., Chea, K. S. & Bohn, R. E. (1999): An Exploratory Study of International Product Transfer and Production Ramp-up in the Data Storage Industry; Report 99-02, Graduate School of International Relations and Pacific Studies, University of California, San Diego. Terwiesch, C. & Bohn, R. E. (2000): Learning and Process Improvement during Production Ramp-up, Warton School, University of California, San Diego. Twigg, D. (1998): Managing product development within a design chain, in: International Journal of Operations & Production Management, Vol. 18, No. 5, 1998, pp. 508-524. Vahrenkamp, R. (2007): Logistik: Management und Strategien, 6th ed., München / Wien, Oldenbourg. Wagner, H. (2006): Kollaboratives Bedarfs- und Kapazitäts-Management am Beispiel der Automobilindustrie: Lösungsansatz zur Sicherstellung der Wandlungsfähigkeit, München, huss verlag.

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Tobias Held von Wangenheim, S. (1998): Planung und Steuerung des Serienanlaufs komplexer Produkte, Frankfurt a.M., Peter Lang Verlag. Wildemann, H. (2007): Anlaufmanagement: Leitfaden zur Verkürzung der Hochlaufzeit und Optimierung der An- und Auslaufphase von Produkten, 5. ed., München, Transfer-Centrum Verlag. Witt, Ch. (2006): Interorganizational New Product Launch Management: An Empirical Investigation of the Automotive Industry, Bamberg, Difo-Druck.

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The Role of Consumer Insight in New Product Development and its Impact on Supply Chain Management: A Swedish Case Study

David Eriksson and Per Hilletofth

Abstract This paper seeks to explore how a profound consumer understanding may influence early stages of a new product development (NPD) process. The issue is examined through a holistic single-case study combined with a literature review. The case study shows how the NPD process is structured and executed in a Swedish furniture company as well as the role consumer insight plays in that process. Empirical data have been collected mainly from in-depth interviews with persons representing senior and middle management in the case company. The research reveals that consumer-oriented, cross-functional NPD in the case company has a strong impact on internal collaboration, and aligns the goals between different departments and functions within the company. Despite inefficiencies on departmental level, effectiveness on company level is achieved. Early indications show an expected growth in contribution margins by 8 percentages.

Keywords: Supply chain management, new product development, consumer insight, demand flow, concurrent design

1 Introduction One of the main objectives with early stages of new product development (NPD) is to search for new areas of consumer opportunities. In order to have a successful output of the NPD process, it is important to acquire a profound understanding of the voice of the consumer (van Kleef et al. 2005; Kärkkäinen et al. 2001; Simonson 1993). Consumer opportunities are amongst the first stages of NPD, and the importance of the quality of the opportunity identification stage is gaining recognition (Cooper 1988, 1998). Comprehensive knowledge about the consumers is needed to understand their true demand (Lee and Whang 2001). However, the knowledge is useless without physical distribution. The linkage between consumer insight and

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distribution activities, supply chain management (SCM) is referred to as value chain management (VCM) (Rainbird 2004). SCM may be described as a set of approaches dedicated to the integration and coordination of materials, information and financial flows across a supply chain (SC), satisfying customer requirements with cost-efficient supply, production and distribution of the right goods in the correct quantity to the right location on the correct time (Gibson et al. 2005; Hilletofth 2009). Without new products, market acceptance and value adding packages, an efficient SC is useless. Hence, the NPD process is closely intertwined with SCM (Hilletofth and Ericsson 2007). Since the value offering is not only restricted to the product characteristics, but also customer service (Christopher 1972), SCM affects NPD. Therefore NPD and SCM must be treated simultaneously (Hilletofth 2008; Hilletofth et al. 2009, 2010; Charlebois 2008; Canever et al. 2008; Vollmann and Cordon 1998; Vollmann et al. 1995; Heikkilä 2002; De Treville et al. 2004). In recent years a new business environment, characterized by rapid and volatile demand changes, short product life cycles, and a high degree of customized products, has evolved to co-exist side by side with the conventional low cost business environment (Christopher et al. 2004). Companies may choose to compete in this new marketplace. To be competitive in this environment a profound understanding of consumer needs, rather than the technology of the product, must be considered during NPD. This challenge calls for innovative and rapid NPD. Customer pain as the driver of all activities is sometimes referred to as demand chain management (DCM) (Bingham 2004; Hilletofth 2009). Further, there is a competitive advantage to gain when customers are included in several stages of the NPD process (Prahalad and Ramaswamy 2000, 2004). The basis for differentiating the SC has been the product characteristics (Fisher 1997). Since not only the product is in focus, the whole value offering must be considered. This calls for innovation and differentiation in several stages during which the consumer comes in contact with the offered product/service (MacMillan and McGrath 1997). The strategy must be reinforced with the activities, e.g. accepting trade-offs and giving the strategy precedence over operational efficiency, all in an effort to escape competition based upon lowest price, with low contribution margins (Porter 1996). The research purpose is to investigate how consumer insight affects early stages of NPD, and its impact on the configuration, and management of the SC. The research questions are: “What are the consequences of NPD that is driven by consumer insight?” and “What impact has a consumer insight driven NPD on the SC?”. The case company is Hans K, a Swedish furniture company, focusing on NPD and distribution. In order to illustrate how consumer insight is collected, and how NPD is structured, as well as the impact it as on the SC a descriptive and explorative holistic single-case study approach is used. In order to gather in-depth data, qualitative methods were used. 114

The Role of Consumer Insight in New Product Development and Its Impacts on SCM

The remainder of the paper is structured as follows: Section 2 is a literature review, Section 3 presents and discusses the research approach and data collection, Section 4 presents the case study findings, Section 5 discusses and concludes the research and proposes new areas for further research.

2 Literature Review Before literature was reviewed a framework was proposed. Many parts of a SC and SCM, e.g. sourcing, and lead-times, are affected by NPD. One part of NPD is design. Hence, design not only affects NPD, but also the configuration and management of the SC. There may also be a strategic choice to be demand driven, or supply driven, which in turn affects both NPD and SCM. Therefore, the proposed framework is that design is a vital part of NPD, and that there are important connections between NPD and SCM/DCM.

2.1 Supply Chain Management and Demand Chain Management SCM is sometimes referred to as a set of approaches coordinating materials, information and financial flows across a SC (Gibson et al. 2005), and sometimes a set of processes dedicated to the same task (Cooper et al. 1997; Lambert et al. 1998). Regardless of definition, there are two ways defined in literature to approach SCM: the lean or efficient approach suitable for functional products, and the agile or responsive approach suitable for innovative products (Fisher 1997; Walters 2006). In order to be both efficient and responsive, a combined approach may be adopted by postponing final configuration (Dapiran 1992; Feitzinger and Lee 1997). DCM has several definitions. According to Walters (2006) it is a matter of emphasis, where SCM emphasizes efficiency in processes and DCM emphasizes effectiveness in the business. Bingham (2004) argues that there are six (from zero to five) key stages of DCM, where the sixth stage is full DCM. In this stage customer pain drives all activities, a profound insight to customers' needs provides a competitive advantage and consumer insight is collected in several ways and spread through the organization in order to orchestrate the customer experience. Ericsson (2003) and Jüttner et al. (2007) stresses the collaboration between marketing and SCM as the focal point for DCM.

2.2 New Product Development The NPD process is a key business process that SCM tries to integrate across the SC (Rogers et al. 2004). Done correctly it allows management to coordinate the flow of new products in an efficient manner across the SC, at the same time fulfilling the demands of the consumers and achieving effectiveness. Moreover, product design may improve the SC capabilities, but the configuration of the SC may 115


also help to improve a NPD process (van Hoek and Chapman 2006). Kärkkäinen et al. (2001) argue that there are three interconnected phases that defines NPD: strategic planning, customer need assessment, and NPD. The strategic planning attempts to ensure correct identification and prioritization of different product development areas generating specific goals for NPD. The strategic planning is based upon the current business strategies with the purpose of clarifying goals before initiating the customer need assessment and the NPD phases to avoid performing the wrong activities. The objective of customer need assessment it to clarify customers' needs as well as the competitive situation for the company. Through consumer insight, companies may not only increase the chance of developing the right products, but also decrease the risk of developing the wrong products (Rochford 1991). Removing the inter-organizational functional focus (silo-mentality) is one way to facilitate creation of customer satisfaction while enabling internal collaboration (Cooper et al. 1997).

2.3 Design Part of NPD is the design phase. Design is defined as “the configuration of elements, material and components that give a product its attributes of function, appearance, durability and safety” (Walsh et al., 1988). Further, the need of fit between activities (Porter 1996) is stressed as design management is defined as the utilization of design expertise in order to strengthen the strategic objectives of the organization (Blaich 1998). It is necessary to coordinate the design resources across company functions in order to fulfill the company's strategic objectives (Vazquez and Bruce 2002). In order to improve NPD a concurrent approach to design is suggested (Khan and Creazza 2009). In concurrent deisgn, design is part of a cross functional approach, design's profound impact on SC is acknowledged and design is therefore constricted in order to create fit with the supply chain.

3 Research Approach and Data Collection This research aims to explore how a profound consumer insight may influence the early stages of a NPD process and what impact is has on the SC. The issue is examined through a literature review combined with a holistic single-case study. The chosen research approach and strategies correspond well with the explorative purpose of this research (Yin 2009). Case study method was considered appropriate since the research analyze contemporary events, capture wider and in some extent new problem areas, and because the researcher has no control over the events (Yin 2009). The case company is Hans K, a Swedish furniture company, focusing on design and distribution of furniture. This company was chosen based on the industry it is operating in as well as its efforts towards developing a consumer oriented NPD process. The case company has actively chosen to compete on a consumer 116


oriented market, with a differentiated and consumer insight driven, product offering as competitive advantage. The choice of market has also included the trade-offs of not being able to serve customers (retailers), and consumers that demand low cost, standardized furniture. One advantage with case studies is the possibility to combine several data collection techniques; in this research qualitative empirical data was collected from various sources to enhance understanding by examining the research object from several perspectives. Firstly, this study is based on data gained from three in-depth interviews with persons representing senior and middle management in the case company; former CEO/founder, CEO, and manager of NPD. In addition, brief interviews with the managers of marketing and purchasing/logistics were conducted to finalize the research. The interviews were conducted in 2009, note taking was the main interview method, the length of the in-depth interviews was 60-90 minutes, and the brief interviews were about 30 minutes. In order to find relevant information the interviews were prepared in a structural way. The interviewees were also able to read the findings from the interview to avoid misunderstandings. Additionally, this study is also based on secondary data retrieved from internal documents produced by the company. Moreover, this study is based on several lectures, meetings, and business trips as parts of an ongoing project between the authors and the case company. The data collection has been documented, which increases the reliability of the case study. However, it should be noted that all case studies are unique and the companies are continuously changing, meaning that the conditions can never be identical. Two tactics have been applied to increase the validity of this study. Firstly, multiple sources of evidence have been used, and secondly, the draft case study reports have been reviewed by the respondents. As shown above different sources have been used to answer the same questions (interviews, meetings, documents), and therefore triangulation can be said to have been used. The use of triangulation has contributed to improving the rigor, depth, and breadth of the results, which may be compared to validation (Yin 2009). Moreover, it also enhances the investigator's ability to achieve a more complete understanding of the studied phenomenon (Scandura and Williams 2000). The overall reliability and validity of the study could have been further improved by increasing the number of informants and extending the period of data gathering to encompass multi-points in time rather than providing a retrospective snapshot. A research protocol was used in order to facilitate future replication. Since the case company is chosen based upon its unique carachteristics, and the findings are based upon contemporary events the findings are foremost generalizable to theoretical propositions (Yin 2009). This study is confined to a low-tech manufacturing industry in Sweden, and attempts to generalize and replicate the findings should consider the business environment of the case company.

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4 Case Study Findings Hans K has two main business areas; NPD of furniture, and distribution of the furniture from Asia to Northern Europe. Hans K stems from Universal Furniture, a furniture distributer founded in 1959. Universal Furniture manufactured in the Far East and had marketing companies in the US, Canada, Europe, the Middle East and Australia. In 2002 the present owners took over the Scandinavian division and became an independent distribution company. In 2004 the company changed its name from Universal Furniture AB, to Hans K. Hans K does not own any own retailers, and their furniture is sold to the final consumer via a variety of stores and retail chains. This leaves a gap in the control of the SC, decreasing the possibility to orchestrate the consumer experience. The company has chosen to disregard the conventional distributor business model, i.e. where companies compete on price delivering furniture specified by the retailer. Instead, Hans K focuses on products developed from a profound understanding of implicit consumer needs. This includes addressing the issues with consumers not being able to communicate what they actually want, rather what they perceive that they want. Implicit consumer needs are found through an appropriate NPD process, developed by the case company. Also, due to a postponement strategy consumers are able to do the final specification on many of the furniture sold by the case company, e.g. change the height and fabric on chairs and the height and size of tables. Hence, a consumer insight driven NPD process had to be developed, and has brought along demands on the configuration of the company's SC. These actions are steps away from producing functional products competing on lowest price, to produce innovative products competing on other terms, such as design and customization. The actions are also signs of the case company working in a demand driven manner.

4.1 Demand Flow Process Hans K illustrates their product management process with a model called the demand flow process (DFP) (shown in Fig. 1). The process incorporates the steps from the strategic market plan and consumer opportunities, that constitute the starting point when developing new products, to the phase out of a product.

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Fig. 1: Demand Flow Process

“The goal with the DFP is to obtain collective, and objective consumer insight and keep the consumer insight undistorted through the NPD process all the way until the finished product is in the hands of the ultimate consumer”, says the founder/former CEO. However, through the process it is acknowledged by the case company that the information is distorted. The main areas of distortion are perceived to be the interface between Hans K sales department and customers, and the interface between the customers and the consumers. Lack of SC control is a source of demand distortion, and increases difficulty orchestrating the consumer experience. The case company also assumes that the quality of the product information, from the case company to the consumer, varies depending through which retailer the information is routed.

4.1.1 Roles within the Demand Flow Process Even though the DFP is clearly defined, the intra-organizational roles are not. The case company is a small company with the founder/former CEO, and father to the current CEO and the marketing manager, still active in the company. With only a few additional people on management level, it has been hard to separate the roles within the company. Due to changes in personnel, intra-organizational roles are currently under revision. Currently the marketing manager is responsible for the consumer segmentation, the manager of NPD is responsible for all NPD projects and restrictions in the materials used in new products, and the manager of purchasing/logistics has the responsibility for the sourcing from Asia.

4.1.2 Strategic Market Plan The SMP is the document guiding the work of Hans K. Within the SMP the consumer segments and the design styles are defined. Consumer groups are defined 119


using psychographic segmentation (Demby 1974), and design styles are divided into three styles. This makes a 3*3 matrix called the product platform. The psychographic segmentation into three consumer groups enables the case company to focus its efforts collecting consumer insight towards targeted consumer groups. Using the product platform aids the case company when identifying in which of the nine segments additional furniture collections are needed, or should be discontinued. The strategy also includes what room to address in a NPD process. The chosen segmentation model is only used to differentiate the design of furniture and treats consumer groups alike in regards of the service offering which may cause the case company to over-serve some groups, and under-serve other groups.

4.1.3 Consumer Opportunities When it is decided what room to investigate, a small group is assembled to do the initial work. So far the groups have consisted of two to three students, studying NPD and design. The group does activities typical for NPD, e.g. trend analysis, customer surveys and consumer surveys. Further, the group also visits potential consumers in their homes in an everyday setting. During the visit, the home is photo-documented. Two of the main goals are to find implicit consumer needs, and to get a base for developing furniture based upon actual, not intended, use. The case company has the knowledge on what to do, and are not reliant on certain individuals to collect consumer insight. Studying consumers, the case company has found gaps between the intended and the factual use of many rooms, and the rooms' furniture. Hence, consumer opportunities previously not known have been discovered, e.g. ventilation in media furniture and a multi-purpose bed end casket with place for dirty laundry, a seat and a surface where a laptop can be placed. The DFP has also lead to completely new furniture collections, e.g. a new collection of entrance furniture. Implicit needs may be one of the best reasons to pursue consumer insight while producing innovative products, and one of the best justifications for a NPD process driven by consumer insight.

4.1.4 Primary Development Hans K has no in-house designers. Instead designers are recruited depending on what square in the product platform is targeted during the NPD project. In most cases, three designers have been recruited. As with investigating consumer opportunities, the case company makes efforts to be able to perform core business processes without becoming reliant on certain individuals. The consumer opportunities are presented to personnel within the case company (CEO, marketing, NPD, purchasing/logistics) and designers in a cross-functional meeting. Designers are not only restricted to a certain square in the product platform, they are also restricted to 120


the use of certain materials. The NPD manager keeps the material choices in a material matrix. This may be seen as a postponement of material choice that helps to secure sourcing from certain manufacturers. Further, it makes it easier for the consumers to mix and match furniture produced by the company, which may increase the consumer perceived value. Solutions to consumer issues are addressed in all furniture collections. Even if the design differs, it is assumed that the day-to-day issues are the same for all consumer groups, e.g. how cables are stored in media furniture. Since the designers work with different design styles, it is perceived that there is no competition between the designers, but that synergy effects emerge. Primary development results in furniture sketches, and technical solutions that are handed over to Hans K in a cross-functional meeting.

4.1.5 Concept Development to Phase Out The manager of NPD is responsible for concept development. Concept development involves positioning on the market, profitability, forecasting, service and logistics. Concept development is followed by product development. This process is rather generic to the furniture business and addresses areas such as product drawings, and product specifications. However, product specifications are not altered based upon cost saving manufacturing measures suggested by the manufacturer. The manager of purchasing/logistics said that: “In order to lower the manufacturing cost, the manufacturer recommended us to change the design of the ventilation in the media furniture, but in those cases we always rely on the information gathered during NPD and stick to our design.” The manager of marketing is responsible for the commercial launch. These activities are formed by the consumer insight gathering activities, and cross-functional meetings, earlier in the DFP. The manager of marketing remembers, and tries to use the ideas found in the homes of the consumers, not only the looks of the furniture, but also the features, when marketing the finished products. The products are marketed using leaflets and folders in the stores, on the company’s web page and through advertisement in different newspapers and magazines. The success of the products is monitored in the product platform. Products that are not profitable, or do not fit the company profile, will be phased out.

4.1.6 Idea Funneling from Consumer Opportunities to Concept Development The steps from consumer opportunities to concept development may be depicted in a picture representing time on the y-axis and idea-with on the x-axis (see Fig. 2). Every step in the process narrows the number of ideas, but at the start of each step there is an increase of ideas due to the cross-functional approach at the case company. 121


Fig. 2: Idea Funneling

4.1.7 Outcomes of the Demand Flow Process As mentioned earlier, negotiating with manufacturers in Asia modifications are often suggested by the manufacturer. The manufacturer might find manufacturing benefits or cost rationalization reasons to justify layout configuration. However, these suggestions are always turned down in favor for the specifications generated though the DFP. For the fiscal year of 2009 an increase in contribution margin of 8 percentages, due to new products developed using the DFP, is expected. This implies that a consumer driven NPD may drive production costs, but also increase contribution margins. Hence, higher cost in manufacturing may be seen as a profitable inefficiency, and the landed cost focus allows managers with different responsibilities to look past their own area of responsibility and focus on the greater good of the company.

5 Discussion and Conclusions The research set out to investigate the consequences of a NPD process driven by consumer insight, and what impact that process has on the SC. The findings are that a consumer driven NPD process aligns internal efforts, prohibiting the silomentality. Departments within the case company are willing to decrease their performance (e.g. purchasing does not accept cost saving modifications to design suggested by suppliers) in order to increase the business output. However, partners in 122


the SC may not realize the possible benefits from the consumer insight driven NPD and lack of collaboration in the SC is believed to hinder ultimate performance. Also, by constraining designers to certain design styles and material choices, coherence in the furniture collections is secured, and reliability in sourcing is increased. Reliability in sourcing may be seen as a risk management tool in SCM. Moreover, with the consumer oriented business approach and NPD process, furniture are developed to be customized by the final consumer. Hence, a consumer driven NPD process has requirements on several parts of the SC configuration. The study reveals that the consumer driven NPD approach has a lot of resemblance to the ideas of concurrent design (Khan and Creazza 2009). However, concurrent design focuses on inter- and/or intra-organizational issues, while the approach of the case company focuses on the collaboration between consumers, designers and the case company, neglecting customers (retailers). Assigning designers to specific tasks and specific material choices has an impact on the balance of power between the NPD process and the design phase. Further, this helps to decrease the risk of silo-mentality since everyone taking part in the development of new products have a window into the homes of the consumers. Clearly, this is in line with steps outlined by Khan and Creazza (2009) to align design with SCM. In contrast to Prahalad and Ramaswamy (2000, 2004) the collaboration with consumers is at an arms-length distance and is restricted to only one part of the NPD. The main theoretical contribution is the combination of concurrent design and consumer driven NPD. Both fields have been researched previously and been found beneficial, but the combination of the two fields still lacks research. It has also been showed that a joint understanding for consumers acts as a catalyst removing silo-mentality while encouraging management by holistic. Moreover, the need for strategic collaboration in the SC is clearly illustrated with the demand distortion in the interfaces between the focal company and its customers, and the customers and the consumers. The finding that a consumer insight driven NPD may be the basis for a shared understanding of the consumer, help to remove the silo-mentality and shift focus to effectiveness is likely generalizable to business environments that do not correspond to the environment of the studied company. The main practical implication is that companies may benefit from taking a new approach to NPD. This includes the co-development of products with the consumers, a concurrent approach to design, and the integration of customers in order to preserve the information integrity. Further, it is made evident that inefficiencies in parts of a company still may improve the main business objectives. The information distortion in distribution acknowledges that good products depend on high quality information flow to leverage the effects of the consumer insight gathering process. Hence, companies embarking on a consumer driven NPD process must consider the configuration of the SC from manufacturing (or earlier) until the goods is in the hands of the ultimate consumer.

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Further studies into the interface of concurrent design and consumer insight may help to propose new and better models for NPD. As of today, these topics are treated separately in literature. Trying to generalize the findings, the context of the case company must be considered. First off, the company is chosen due to its carachteristics and not by a statistical method. Secondly, the context in which the case company is active should also be considered. Future research in this area is of interest. However, there are several outside factors that must be regarded, since there is a big risk of misinterpretation between significant and non-significant factors. The case company’s position in the SC, a distributor/NPD company coordinating goods flows from Asia and finished goods flows in northern Europe raises a lot of questions of on the two parts of the SC. How does an innovative NPD process fit with sourcing from low cost countries in Asia? How should distributors be treated with regards of possible distortion in the downstream information flow and how does the information distortion affect how the consumers perceice the value of the furniture? It is likely that the benefits of an innovative NPD are strongly dependent on the overall SC configuration. Further, while a new approach to business may open new markets and give companies competetive advantage, the cost of the process might reduce the advantage. Also, in markets that are not mature and demand is abundant, there may not be an incentive for differentiation and innovation. It is obvious that the choice to change from a low-cost to an innovative strategy should include factors from the surrounding business landscape and not only internal motivators.

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The Balanced Scorecard as a Measure of Performance: A Case Study on a Shoe Industry Sector

Leonardo Perazza, Paulo Cesar Chagas Rodrigues

Abstract In the last decades, meaningful changes have been noticed in the business world. These are due the increasing demanding of costumers and the international political and economic moments that have generated a market dynamic which is growing unstable and contributing to increasing challenges referring to the understanding of demands. Therefore, companies considered pioneers chase to adapt the management model of operations to this new reality. Considering that the balanced scorecard transmits the vision and strategy trough a set of perspectives, including measuring the expected results and processes that will lead to future results, this paper aim was to evaluate the operation management model through the balanced scorecard method, aiming to reduce the costs of productivity and increase competitivity. This search was restricted to the analyses of the influence of the operation management of a medium size company, in the productive segment (shoes factory sector) and also related to the geographic focus (the city of Jaú based in the center west of the state of São Paulo). The study case took place in a shoes company in Jaú, with an average of 120 direct employees (factory’s employees) and around 50 indirect employees (outsourcing services), besides some seasonal employees, that sum, approximately, 180 employees, the a semi-opened questions survey, with the aim to collect information and data from the main managers of each area of the company. After a cross analyze between the theorical references and the study case, it was concluded that the demands for improvement of the performance inside organizations of goods and services made the approaches related to the operation management to evolve through the years, becoming a wide and net vision in the management of a business, perceiving the company as a whole, contributing, therefore, to improvements in the condition of growth and sustainability of the organizational activity. It is emphasized, therefore, the necessity of using all resources available, minimizing problems and maximizing opportunities.

Keywords: operation management, balanced scorecard, measuring of development.

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Leonardo Perazza and Paulo Cesar Chagas Rodrigues

1 Introduction The business environment, particularly in the footwear industry Jau, has spent the last decades, for significant changes, they increase the competitive level of demand from customers, at times political and economic world and the dynamic nonmarket increasingly unstable, creating for companies increasing challenges in understanding the demands. With the entry of Chinese products in Brazil, the quality of domestic products had to undergo a new adaptation, since the products using imported raw materials and labor force cheaper and, therefore, the level of dubious quality. In order to compete on price level with the Chinese, the footwear industry Jau started to develop products of high benefit, thus expanding its production to meet the higher social classes. In order to maximize operational processes, we used the analysis of operations management balanced scorecard method, which helped identify the elements necessary to reduce costs by improving processes. From this context, the model management operations are being adapted by firms considered pioneers as a way to fit the new political and economic world, becoming a focus of academic study and implementation by other companies. Starting from these premises were to study the mutual influence of the demand management and production systems, with the main focus of this work, introducing the key elements of each of these processes and their interactions: – – –

As operations management influence the production system without having to generate new costs? As the cost of imported goods bearing the footwear industry Jau? As the method Balanced Scorecard (BSC) can help to maximize their operations?

The aim of this study is to analyze the operations management performance by the method of Balanced Scorecard, a company in the footwear sector in the city of Jau, in order to identify key characteristics that may affect the cost of productivity and competitiveness. This research was restricted to analysis of the influence of operations management in a midsize company in the productive sector (footwear industry) and also in relation to geographical focus (the city of Jau in the central-west of São Paulo). We used a literature review of the literature, research methodology to model a semiopen, and also the case study. A scientific paper should include references, a review of literature to support the work of research and exploratory research and search and collection of information is systematic, for methodological work, or unsystematic, which does not provide clear and specific targets. (Santos; Rossi; Jardilino, 2000). (Santos; Rossi; Jardilino, 2000). 128


The following study used a methodology of quantitative and qualitative second Mioto Lima (2007), it is imperative to follow paths not random, because such research requires a high degree of critical vigilance of observation and careful selection and routing the methodological procedures. We also used the case study, which to Yin (2005) case study is a case study that investigates a current phenomenon within its real context in which the boundaries between phenomenon and context are not clearly defined. According to this author, should be used multiple sources of evidence (A semi-structured, in-situ observation and analysis of documents) as evidence arising.

2 Management Operations According Cavenaghi (2001), the requirements for improved performance within organizations for goods and services have made the approaches to operations management evolved over the years, becoming a broad and network management in the business, for an overview of the company as a whole, thereby contributing to improvements in the condition of growth and sustainability of organizational activity. The concept of operations, addressing the process, according to Evans (1997), is a sequence of activities that produced a physical good, service or information to the consumer. Transforming customer needs for improvements in products hitting the high degree of satisfaction, seek new information technology to improve productivity and processes while avoiding waste, develop skills, adapt, and motivate employees through human resources practices. According to Johnston and Clark (2002), operations management also involves the management of processes, people and resources to provide quality goods and low cost. According to these same authors, the operations manager must develop strategies for future operations to compete and / or follow into the future, find ways to motivate people in order to increase productivity without changing the quality of service, managing the daily operations performance required. Corrêa and Corrêa (2005), argue that operations management handles the strategic activity of scarce resources (human, technological, informational, and others), the processes that deliver goods and services, meeting the needs of quality, time and cost to its customers and match these goals with efficient use of resources that the organization requires. These authors propose to treat the management of operations under the following aspects: – – –

Addressing the strategic management of operations as a whole; Addressing management operations as a "value package" for the client (physical goods and services) Understanding that the management of operations belongs to a network of operations that interacts with the system that serves the End User, ensuring that it is well served by encouraging their choice. 129


For Cavenaghi (2001) then, Operations Management is the planning and ongoing control of people and resources, which involves decisions at all levels, to meet the needs of the End User.

3 System Performance Measurement According to Neely et al. (1995), a system of performance measurement should include measures individual inter-related, belonging to a particular environment, as shown in Illustration 1. When doing this project, one must ask these question: – – – –

What performance measures will be used? For they be used? How much will they cost? What benefits will provide?

Environment

Measure Individuais

Measure

Measure

Individuais

Individuais

Measure Individuais Measurement System Performance

Source: Neely et al, 1995 Fig. 1: A framework for the design of measurement system performance

To Lebas (1995), performance management is an organizational philosophy, supported by performance measurement. There is an interactive process between the two issues. The approaches are different, however, performance management is concerned with issues such as training, incentives, communication, as performance measurement, assesses the potential, entries, results and variances. 130


Bitici, Carrie and McDevitt (1997) consider that the system of performance measurement is the central information system of the process of performance management, where the organization manages its strategic and operational performance, in order to promote a proactive system of control still business, activities, tasks and people, and feedback is obtained through the measurement system performance by allowing an appropriate management decisions. For Martin (1998), the process of performance management is a means used for the organization to manage its performance, along with corporate and functional strategies and objectives. The competitive environment demands innovative products in technology and short life cycle, and therefore performance management is aligned to concepts: – – – –

Recognition of manufacturing as a source of competitive advantage; Total Quality Management products and processes; Company dedicated to the satisfaction of its stakeholders; Competitive priorities: quality, cost, reliability, time, flexibility, innovation and service;

According to Martins (1998), the system of performance measurement is the center of the process of performance management that integrates all of the systems development and review of strategy, management accounting, management by objectives, performance measures, non-financial structure of incentives and bonus for individual performance. Martins (1998) lists the characteristics of new systems of performance measurement: – – – – – – –

Equivalence with the competitive strategy; Drive for continuous improvement; Identify progress; Be intelligible to the employees; Cover the whole process of supply chain; Information in real time; Evaluate the group and influence the attitude of employees.

To run and run (2005), systems of performance measurement is the cycle of planning and control, essential for the management of operations, therefore, provide information about the performance that after evaluated, support the process of decision-making. According to Corrêa and Corrêa (2005, p. 100), the establishment of an adequate system of performance evaluation is also important in influencing desired behaviors in people and systems operations for certain strategic intentions are more likely to actually become actions aligned with the intended strategy. 131


4 Balanced Scorecard According to Kaplan and Norton (2001), the BSC transmits the mission and strategy held in different perspectives: financial, customer, internal business processes and learning and growth. Namely, the financial perspective is the guiding of the other, reported by strategy maps. Niven (2002) defines the Balanced Scorecard (BSC) as a set of measures derived from the organization's strategy, a model for leaders to use in communicating with employees, customers and suppliers about the results for which will achieve its mission. As the BSC a system of measures, a strategic management system and a communication tool. According to Johnston and Clark (2002), the BSC is a model best known for encouraging managers at all levels to invest in a more balanced set of measures. "The Balanced Scorecard to focus on specific measures selected to represent the organization's strategy" (Kaplan, 2005, p.42). For Marchesan, Miorando and Caten (2006), the BSC seeks a solution to conflicts between the goals of short-and long-term strategic system. Thus, the goals represent its mission, as the basis of the indicator system. According to Kaplan and Norton (2001), each organization achieves its alignment and strategic focus in different ways, places and sequences, using the five principles, described in Illustration 2. Also according to Kaplan and Norton (2001), organizations are in numerous sectors, business units and departments that have their own knowledge and culture. According to these authors, these divisions are the main barriers to implementation of the strategy, because there is great difficulty in communication and coordination between them. The organizational performance should be more than the sum of the parts and the individual strategies must be linked. For Kaplan and Norton (2001), all employees must understand the strategy and lead the day-to-day processes, contributing to the success of its implementation. Executives can begin this process by using the BSC to communicate and educate the organization in the strategy to be implemented. According to these authors, the strategy must be carried out through a double process continuous. Organizations introduce a process to manage strategy, integrating the management tactics with management strategies, using three processes: link strategy to budgeting processes, the process of reviewing the strategy and learning and adaptation strategy.

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5

Change through executive leadership

4

1

Transmit strategy to operational terms

Strategies for continuous processes

BALANCED

strategy

SCORECARD

2 Organizational alignment to the strategy

3 The strategy for the work of all

Source: Adapted from Kaplan and Norton (2001) Fig. 2: The principles of organization focused on strategy

For Kaplan and Norton (2001), are the following key strategic themes: – – –

Revenue growth and mix: refers to the expansion of products and services, offering options of higher added value and changing its pricing strategy; Reducing the cost / productivity improvement, which refers to efforts to reduce direct costs and products and services and optimize the use of resources; Asset utilization / investment strategy: attention to the reduction of capital employed for growth, reallocate resources and exempt assets without adequate returns.

For Mendes (2002), goals and financial measures in a double role in setting the desired performance of the strategy, serving as a target for the goals and measures for all other perspectives of BSC. The Illustration 3 lists the financial goals with the other perspectives.

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STRATEGY

GOAL

RESULT

FINANCIAL PROCEDURES FINANCIAL TARGETS FOR

CUSTOMER CASES

LONG-TERM

DESIRED PERFORMANCE ECONOMIC

INTERNAL PRO-

LEARNING

PRO-

Source: Adapted from Kaplan and Norton (1997) Fig. 3: Objectives and performance long-term economic

According to Kaplan and Norton (2001), in the customer perspective of BSC, the focus should identify where the business units will compete and measures the performance of these targeted segments. The main outcome measures are: – – – – – –

Satisfaction, retention and customer acquisition; Customer profitability; Market-share of the targeted segments; Time and reliability in service; Flexibility to create new demands; Development of new services.

Although the client perspective, Kaplan and Norton (2001) discuss the concept of offering value to customers, which represents the attributes that they can offer to build loyalty and customer satisfaction such as functionality, quality, price and time, requiring focus on critical internal operations to meet the needs of customers and about the prospect of internal business processes is to identify critical processes, the organization must achieve excellence, enabling business units meet the offering of securities that will win customers and meet the expectations of investors in financial return. Kaplan and Norton (2001) show a model that companies can customize their internal process perspective, identifying customer needs and meeting them on three main perspectives:

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– – –

Innovation process: identify the market and create the product / service; Process operations: building and supports the products / services; After-sales: customer service.

According to Niven (2002), it is necessary to identify the key internal processes that will provide excellence in order to continue adding value for customers and shareholders. The prospect of learning and growth, according to Kaplan and Norton (2001), to identify the infrastructure that the organization must build to create long-term growth to improving their skills to improve quality and adding value to customers and shareholders. She comes from three sources: – – –

People; Systems; Organizational procedures

From the perspective of learning and growth, Kaplan (2005), the focus of measurement would be related to the goals as satisfaction, retention and employee productivity. To Niven (2002), the prospect of learning and growth is the basis for other perspectives, as it covers the ability of developers and information systems that are the basis for achieving the results you require other perspectives. Kaplan and Norton (1996) argue that the BSC transmits the vision and strategy through a set of perspectives, including measures of expected outcomes and processes will drive for future results. For these authors, the four perspectives are most important to demonstrate the organization's results, however, there is the possibility of adding one or more perspectives, since other parties may be important in the business strategy. According to Kaplan and Norton (1996), there are two important indicators in the CSD: the outcome indicators (lagging indicators) that show past performance and the effects of decisions, and leading indicators (leading indicators) that show what should be carried out to obtain long-term results. Kaplan (2005) associates the BSC model to the model McKinsey 7-S, which provides seven factors critical to the implementation of the strategy: – – – – – – –

Strategy; Structure; Systems; People; Skills; Cultural Organization; Shared values. 135


According to the analysis of Kaplan (2005), both models have a synergy, they require a multidimensional approach. They have a relationship of cause and effect and help managers direct their organizations to effectively implement the strategy. Kaplan (2005) concludes that the BSC can also help implement the use of the McKinsey 7-S, broadcasting the seven factors of the model by means of measurable goals that will lead to action and feedback. Attadia, Canavarolo and Martins (2003) believe that the successful implementation of the BSC depends on factors such as conceptual little-explored factors related to vision, entrepreneurship, the game of power, influence of culture and leadership. According to these authors, other criticisms are related to structural failures relating to the configuration of the BSC as a lack of detail in the development of performance measures, lack of detail in data collection and lack of insight into the actions of competitors. Finally, the authors cite the reviews as managerial failures of management in implementing the BSC: translating the vision, communication and networking strategy, business planning and feedback and learning. Voepel, Leibold and Eckhoff (2006) Critics of the Balanced Scorecard model saying that the model has a static structure that forces the existence of only four prospects and therefore does not adapt to changes in the new economy and that, being a routine processes, does not stimulate the creativity of employees. Responding to these criticisms, Kaplan and Norton (2006) argue that in the chapter "Four Perspectives: Are these sufficient?" Was envisaged that some organizations may use more of other perspectives, according to its merits and according to these authors, firms may using the BSC model to adapt their strategies, gaining knowledge and economic conditions, generating new ideas from the organization. Finishing the criticism, Voepel, Leibold and Eckhoff (2006) argue that the BSC has a mechanistic and linear thinking difficult performance in modern business, where networks and interconnections are increasingly present. They suggest that companies rethink their creations with their own system of measurement. Kaplan and Norton (2006) counter that the authors violate the principles of the academy, they encourage organizations to replace a model tested and proven around the world for a model without reference publications that claim to have been successful only in an organization. Pietro et al. (2006), says a survey conducted in the field, that 93% of the factors for the failure of the implementation of the Balanced Scorecard is the lack of commitment from top management. According to these authors, other critical situations highlighted the discussions are not clear and infrequent, not using the BSC as a continuous process and not the division of responsibilities. Although the Balanced Scorecard has been used in large enterprises around the world, the climate and other ideas and models have been placed on academic and scientific. Voepel, Leibold and Eckhoff (2006) suggest the abandonment of the companies, however, the set temperature can be used constructively in order to 136


provide improvements in applications along with other existing models or on the rise.

5 Case Study The case study was carried out in a footwear company Jau, through data collection, which was based on a standard questionnaire with semi-open. O intuito deste modelo de questionário é poder coletar informações e dados junto aos principais gestores de cada área da empresa. The purpose of this model questionnaire is able to collect information and data with key managers of each area of the company. The history of footwear Jaú began in the nineteenth century with the arrival of an Italian who installed the first shoe store in town. At this time, there were a handful of leather and footwear were made on a full scale. In 1943, the historical data was based industry first legally constituted and, shortly thereafter, there were many others, established by those who were employees, in Illustration 4 shows the evolution of the production process which merges the craft process and the mechanical.

Fig .4: Photo of the manufacturing process of sandals

Footwear manufacturers have begun to gain some political projection, having elected, years later, Mr. Jarbas Farracco, Mayor of Jau, 1968 to 1972. The industries have evolved and the work initially craft, have been carried out with the aid of high-tech machines. In 1979 he founded the Association of Footwear Industries of Jau, to defend the interests and represent the business sector. Since then, the number of companies grew, and today, Jau is known as the Shoe Capital Male. It is estimated that there are about 250 industries, responsible for generating over 16 thousand direct and indirect. The footwear sector now accounts for more than 40% of the GDP of the city, being a major contributor to the economic and industrial development.

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The city of Jau houses a concentration of industries of women's shoes with 90% specializing in products made of leather, as well as companies that supply chain, educational institutions, technical support and financial and other companies that feature a Local Productive Arrangement (APL). The APL consists of approximately 1182 formal establishments, in which 250 companies are women's shoes, 800 newsstands Service, 120 companies of shoe components, leather, companies of leather and 3 malls with 175 stores shoes. Together these companies generate about 17 thousand direct jobs, divided by 8390 at the Footwear Industry, 4000 on newsstands service providers; 1400 in parts companies, 80 in the tanning of Jau, 100 enterprises and artifacts; 400 jobs in the malls. The production of APL is approximately 130 thousand pairs per day, with capacity to increase production by 30%. The footwear sector now accounts for more than 40% of the GDP of the city, being a major contributor to the economic and industrial development of the municipality. The company submitted the study is characterized by a manufacturing industry of women's shoes of various types such as Mules, Scarpins, Chanel, Peep Toe, Shoes, Sandals, Boots, Strains, and Anabelas Rasteiras in Table 1 and Illustration 5 is shown percentage production of each model. It has approximately 120 direct employees (employed at the factory) and about 50 indirect employees (outsourced services), plus a few seasonal employees, which total approximately 180 employees. The company has a large share of activity in large networks (or magazines) and, moreover, also has representatives who work in Brazil, with a maximum coverage area is in the greater Sao Paulo and Rio de Janeiro. Type

Qtd.Modelos

%

Season

Sandals

40

22%

Summer

Creeper

35

19%

Summer

Peep Toe

25

14%

Half-season

Cepa

12

7%

Half-season

Anabela

12

7%

Half-season

Slipper

12

7%

Half-season

Scarpin

15

8%

Winter

Mule

12

7%

Winter

Chanel

12

7%

Winter

Bota

5

3%

Winter

TOTAL

180

100%

YEAR

Tab. 1: Types of models manufactured by Company A in each station

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Initially, the company was setting up family, with few employees, little machinery, reduced physical space and with little administrative structure. But with the development and growth were set general policies that caused it to cease the main features of a family business, which made today a very structured company.

Tipos de Calçados

7%

7%

7%

8%

7% 7%

14%

Sandália Rasteira

3%

Peep Toe Cepa

19%

22%

Anabela Sapatilha Scarpin Mule Chanel Bota

Fig. 5: List of types of models manufactured by A

The company currently has 10 types of shoes, which generate about 180 models, which can be produced without difficulty purchasing raw material, which is one of the main reasons that make a collection to be abolished to make way for a another, with new trends in materials and fashion. The variation of modeling is determined by the seasons and the fashion trends. This makes the process very dynamic, especially in today's market, which is increasingly demanding as new products. For the production of women's shoes, the stations are considered as follows: – – –

Winter: it has a specific modeling for the climate, with more closed shoes; Summer: also has its specific modeling, which is always easier to produce the shoes having a more open construction; Fall / Spring is considered half-season for production purposes, with semi-open shoes, that meet the temperature changes of this period and in the regions served.

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The board is responsible for making important decisions, or that involve drastic or sudden changes in some of the business processes that may affect in the end items such as: Quality, Quantity Production, Value Billing, and each sector or department within the company has a manager or boss who is autonomous and is responsible for decision making smaller, day-to-day and affecting only a small part of a certain process thus not affecting the company in general. There is a pre-defined production as the industry should reach its daily goal to keep the values of a stable cost for the company to not pass a loss with the loss of production, since fixed costs are linked and calculated directly as a function of total daily production. All this strategy is reviewed weekly by all managers and leaders of industries that come together to try to develop and implement strategies that can help better the difficulties of all sectors involved in the process. As the strategy of the production process, there is also a strategy to achieve competitive advantage. Very important in today's market where there is large supply of cheap goods coming mainly from other countries with China, for example, some measures are critical to achieve competitiveness as a good choice of suppliers of raw materials that have the agility and quality of delivery and competitive prices, to avoid wasting time and materials are mainly used properly of them, get good prices of raw materials by buying and planned large amount of forming partnerships with suppliers and even customers and also make a good balance of laborcost labor (for some production processes) and labor-skilled (high quality) to ensure that this is actually done, in Figure 6 is shown the process of sewing leather compose a women's shoe.

Fig. 6: Process sewing

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The company's mission is to always keep the focus on excellent service and quality products with competitive prices, to become an increasingly strong company with good partners in order to become a leader in the shoe industry and female fashion. Its main objective of operations strategy is to carry what is designed on paper to reality of a production, following all the steps in the pre-defined strategy. The main indices used in the company as measures of process performance are: Production Quality and Quantity of Production. Each part of the company has a daily control of how much was produced in that process and the level of quality was obtained for this quantity. It is taken into account the number of defects found at the end of the process, the number of couples with poor workmanship and other minor factors. In all sectors of production are made to measure performance: Modeling (Technical): there is a number of models prepared and how many of them have problems in the production process; Warehouse: there is the agility in the supply of production and that as this occurs, if there are missing parts or materials at the entrance of the item in production; Court: There is a quantity of cut and how any waste or use thereof, and stitching: there is a number of pairs sewn on and of those, what percentage of defects caused by poor quality in the process, and finally the assembly: there were many pairs of shoes were assembled at the end of the day and again the amount of material defect or wasted in the process by poor management materials, in Illustration 7 we can see how is the quality test, in which the official inspects the naked eye product to product.

Fig. 7: Process quality analysis

This performance measurement has as main objective, to oversee all cases individually to see if everyone is reaching satisfactory levels of performance of each sector, because if you have any kind of problem of any kind, it can be detected easily and taken the necessary steps to that sector falls within the standard of the company without compromising the entire process of production. The organization manages its performance, together with corporate and functional strategies, and objectives, because everything is part of a single context closely related to each other. The 141


company can never achieve the goals if the performance or strategies are failing, the strategy will never work if performance is bad, satisfactory performance will never occur if the strategy is wrong. All administration is always paying attention to these factors as a whole company. For industry, a string of values representing the set of activities performed by the company from its dealings with suppliers and production cycles and selling to the phase distribution of the product. It's all action that is needed to transform raw material into final product is well made and that adds value not only money but also the intangibles such as product awareness. You can identify the link between long-term strategies with short-term actions, for all short-term action that is performed, except that some are influenced by the drastic change of the economy, is an action aimed at improvement of the production process to achieve strategies and long-term goals. The company seeks to continually improving and refining the same way that the change strategies and objectives are achieved. These traces are new goals, and continues the cycle indefinitely and all this happens with short-term actions that at any given time will achieve the long-term strategies. With the help of the growing industry of Information Technology, both in the area of software and products and the area of training courses, virtually all sectors of the company communicate through instant messaging software and e-mail. This causes the productive and administrative processes should be linked with greater efficiency and safety, since all sectors are getting all the information that is part of the process. For the functionality of the system has a communication management for a specific career, which guarantees the quality and safety standards. The outlook for the financial processes are geared to capital growth and cash flow while maintaining the financial health of the company and achieve stability in the marketplace. For internal processes, the prospects are aimed at continuous improvement of production processes, seeking the overall quality of the final product, reducing gaps between processes, in addition to ongoing concern about the satisfaction of employees and waste production that will affect their environment. The growth and learning, the prospects for a steady flow of technological developments in machinery and computer equipment, training of skilled qualified workers within the company to the management of courses and technical information given to employees. In relation to the customer perspective, these aims the development of products that have a high level of acceptability and quality, and delivery days in what is proposed by them, trying to get a strong brand and market knowledge. For this organization, the prospect of achieving excellence in product quality and the same quality production for all parties involved, from the making of the display, sales, processing, production, final product and customer is very important for the end customer, satisfied, can serve as marketing.

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6 Conclusions The theoretical framework was useful for the study, since it allowed a more critical view on the subject studied and the behavior of footwear companies that seek to maintain its production level, partnerships between suppliers and customers, in order to keep deadlines scheduled deliveries and the growth of its capital, different from that proposed by the authors of the bibliographies studied. Through interaction with the company, we can see that but measurement of the performance of competitive dimensions such as cost, quality, speed, among others, were important, the resulting information would be of little value if they were not suited to organizational needs. Although the cost reduction is considered important, the company's main objective is to maintain quality in their manufacturing and production quantity. The model analyzes the balanced scorecard performance management of the companies on four perspectives: financial, customers, processes and learning, these perspectives are not viewed clearly in the industry studied. The company is interested in cost reduction, from the moment that's going to rework some sections, the time of manufacture of shoes is beyond the preset limits on the strategy and the purchase of raw material costs are exceeding the originally calculated . The management of operations, mainly using of the model can capture the value that the company does need to insert into their final product, or add attributes to shoes, the services provided customer service and image that the company is to customers. And for that, it is necessary to generate new costs, and yes, identify the real mission of the company, which is seen and followed by all levels (strategic, tactical and operational). For the company studied, may also be noted that there is a pre-defined as the actions of short and long term, since the entry of imported products at extremely low costs, industry has innovated and created a "half-season "to make new products, thus leaving the normal pattern of industries in the same sector. This provides continuous changes in production, adapting to ever to market requirements. Following the concepts of the BSC, the industry can maximize its operations without financial costs there are surplus, measuring the operating performance of each sector and directing one to a predetermined goals, so that every problem is easily detected and taken appropriate action to that sector falls within the pattern of the company without compromising the entire process of production. Because of that, the shoe industry in question is not totally out of context studied, however, it is necessary to readjust some sectors through the implementation of the BSC in its strategic management to increase its competitiveness in the market, keeping ahead of new trends in management of operations.

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References Attadia, L. C. L.; Canavarolo, M. E.; Martins; R. A. (2003) Balanced Scorecard: Uma análise crítica. In: Encontro Nacional de Engenharia de Produção, 23, 2003, Ouro Preto. Anais... Ouro Preto: Abepro. Cavenaghi, V. (2001) Gestão do desempenho empresarial: A contribuição da área de manufatura. Tese (Doutorado em Engenharia de Produção) Programa de Pós-Graduação em Engenharia de Produção, USP, São Paulo. Corrêa, H. L.; Corrêa, C. A. (2005) Administração de Produção e Operações: Manufatura e Serviços: uma abordagem estratégica. ed. compacta, São Paulo: Atlas. Evans, J. R. (1997) Production Operations Management: Quality, Performance and Value, 5th ed. St. Paul: West. Johnston, R.; clark, G. (2002) Administração de Operações e Serviço, São Paulo: Atlas. Kaplan, R. S.; Norton, D. P. (2001) Transforming the balanced scorecard from performance measurement to strategic management: Part II. Accouting Horizons. v.15, n.2, p. 147-160. Kaplan, R. S.; Norton, D. P. (2004) Mapas Estratégicos: convertendo ativos intangíveis em resultados tangíveis. Rio de Janeiro: Campus. Kaplan, R. S.; Norton, D. P. (2006) Response to S. Voepel et al. “The tyranny of the Balanced Scorecard in the innovation economy”. Journal of Itellectual Capital. v.7, n.3, p. 421-428. Kaplan, R. S. (2005) How the balanced scorecard complements the McKinsey 7-S model. Strategy & Leadership. Chicago, v.33, n.3, p. 41-46. Lebas, M. J. (1995) Performance measurement and performance management. International Journal of Production Economics. v.41, p. 23-35. Lima, T. C. S.; Mioto, R. C. T. (2007) Procedimentos metodológicos na construção do conhecimento científico: a pesquisa bibliográfica. Revista Katál. Florianópolis, v. 10, n. esp., p. 3745. Marchesan, C. H.; Miorando R. F.; Caten, C. S. (2006), Building Competitive Advantage using Performance Evaluation. In: International Conference in Industrial Engineering and Operations Management, 12., 2006, Fortaleza. Proceedings... Rio de Janeiro: Abepro. Martins, R. A. (1998) Sistemas de Medição de Desempenho: Um modelo para Estruturação do Uso. 1998. Tese (Doutorado em Engenharia de Produção) - Programa de Pós-Graduação em Engenharia de Produção, USP, São Paulo. Mendes, D. P. (2002) O Balanced Scorecard como instrumento de avaliação do nível de desempenho logístico em uma empresa de prestação de serviços. 2002. Dissertação (Mestrado em Engenharia de Produção) – Programa de Pós- Graduação em Engenharia de Produção, UFSC, Florianópolis. Niven, P. R. (2002) Balanced Scorecard step-by-step: Maximizing Performance and Maintaining Results, New York: John Wiley & Sons, 2002. Neely, A.; Gregory, M.; Platts, K. (1995) Performance measurement system design. International Journal of Operations Management. Cambridge, v.14, n.4, p. 81-114. Prieto, V. C.; Pereira, F. L. A.; Carvalho, M. M. C.; Laurindo, F. J. B. Fatores críticos na implementação do balanced scorecard. Gestão & Produção. v.13, n.1, p. 81-92, 2006. Santos, G. T.; Rossi, G.; Jardilino, J. R. L. Orientações metodológicas para elaboração de trabalhos acadêmicos. 2 ed. São Paulo: Gion Editora, 2000. Voepel, S. C.; Leibold, M.; Eckhoff, R. A. The tyranny of the Balanced Scorecard in the innovation economy. Journal of Intellectual Capital. v.7, p. 43-60, 2006. Yin, R. K. Estudo de caso: planejamento e métodos. 3 ed. Porto Alegre: Bookman, 2005.

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Case Study on Inventory Management in a Small Manufacturer of Auto Parts

Nicolle da Silva Panzuto and Paulo Cesar Chagas Rodrigues

Abstract The objective of this study was to analyze the production process and supply control in order to identify possible gaps and develop a method for managing supplies, which can be achieved. The relevance of this research on the benefits that the company can obtain by identifying the problems of supply control, allowing the development of solutions. The research method used was the case study, which was grounded on the tripod semi-structured interviews, on-site observation and document analysis, this methodology was very suitable because it can be analyzed and cross checking. During the semi-structured interview, the point of view of the respondent can be seen without any interference by the interviewer. The possibility of implementation of the proposal obtained from the theoretical framework that together with the complementary actions suggested here, in order to make it more productive and profitable. This work allowed them to observe the weaknesses in managing the supply chain and what the points to work should be. It allowed using some scientific models in the company object of study in order to improve supply management.

Keywords: inventory management, planning and control, Make-To-Stock, supply chain management.

1 Introduction Small businesses are forced to develop technologically and managerially to increase their earnings and, therefore, expand its consumer market. The models of inventory management are differentiated by the degree to which the variables represent reality, for example, volume and size of the stored charge, economic lot of buying and production and demand forecasting. The companies most concerned with inventory management take into account aspects such as production rate / receiving materials, uncertainties in demand and in time, changes in price / costs based on the quantity purchased / produced, number of distribution centers, among other factors. 145


The inventory management has strategic importance for business success since it gives the media more diverse production systems by increasing or reducing inventories and generating factor of production and financial gains. In order to reduce costs, increase productivity gains and to adapt the characteristics of products and production processes to market needs, small businesses are under pressure to review their production models to provide greater reliability and profitability. This research is restricted to the analysis of inventory management in a small company, whose manufacturing plant is located in the city of Bauru. Thus, we sought to define the scope of analysis to the object being studied (inventory management), in relation to the productive sector (auto industry) and also in relation to the geographical focus (Bauru / SP). The issue will be addressed in this research is the lack of planning in the production process and inventory control influence the management of stocks in a small business.

2 Supply chain management The management of the supply chain aims to manage, coordinate, develop standards and benchmarks so that all work satisfactorily, seeking to reach the ideal balance between supply of raw materials, finished products and consumption. Being responsible for planning and controlling the flow of materials, this aims to maximize the use of company resources (ARNOLD, 1999). In which the control function is defined as a flow of information to compare the actual result of certain activity with their outcome. This flow of information can be visual or oral, but it is recommended to be documented in order to be considered filed and retrieved when needed (FRANCISCHINI; GURGEL, 2002). According to Rodrigues (2008), indicators that support process management, varying according to the company, the complexity of products, market behavior and management of the supply chain. According to Castro (2005), the economic lot EOQ (Economic Order Quantity) was developed by Ford Harris in 1913, based on the logic that the optimum amount to be produced is one that has both the lowest order cost and inventory that matches process itself the product preparation (set up), load (cargo) and issuing the request. As Severo Filho (2006), the main assumptions of the classical formulation of the EOQ are: (a) the demand is deterministic, constant and continuous, (b) the replenishment lead time is deterministic and constant, (c) shortages of goods and backorders (late deliveries) are not permitted, (d) order costs and inventory are independent of the size of the order and do not vary over time, (e) the request comes complete in a single instant of time, (f) miscellaneous items are asked independently, i.e., are not considered the possibilities of an application on multiple items and (g) there are restrictions, such as storage and transport capacity. 146


To Francischini and Gurgel (2002) the administrator of materials to decide which batch size that the company will need to purchase or manufacture, so that quantitative variables that optimize the total cost and qualitative variables that are internal and external customers. According to Christopher (2009), economic lot purchase (LEC) seeks to channel that there is a quant old "optimal" applications. The LEC reaches this optimum balancing the cost of maintaining inventory with the cost of issuing a request for refueling and the cost of preparing the production, according to Equation 1. LEC 

2.Q.C P Ce

(01)

Where: Q amount of time in units; C p unit cost of the application; C and cost of maintaining inventory in the period, per unit. According to Stevenson (2001), the LEC is used to identify the size of the application that will minimize the total cost of maintenance and ordering of stocks. This is one of the most basic models to be used. Model LEC determines the optimal volume of resources applied to items stored in other words, the LEC determines the volume of stored items that minimizes the total cost. According to Rogers, Rogers and Ribeiro (2004), the assumptions of this model can be summarized as follows: (a) Receive instant requests, (b) there is no discount, (c) there are only two types of costs, (d) not rationing resources, (and) prices are constant, (f) Each stock is analyzed independently, (g) constant demand, and (h) there is no risk. Because of the importance of the risks of demand forecasting are related to any lack of stocks and the consequent loss of sales, has a measure of preventive maintenance to determine an amount of safety stock (S), medium stock (MS) , stock (Emax) and minimum inventory (Emin) to meet unforeseen demand (ROGERS, RIBEIRO, ROGERS, 2004). The variable K is the value of the level of efficiency regarding the fulfillment of requests, i.e., if the stock of the company comply with the request of the production. Exposure to risk increases as the decreases. The equations 2, 3, 4 and 5 describe how to determine the volumes: ES  CxK

EM 

LC  ES 2

(02) (03)

E max  ES  LC

(04)

E min  ES  K

(05)

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Where: ES = Safety stock MS = Average Inventory E Max = Maximum stock Min E = Stock Low C = Average consumption in the K = Coefficient of service level Q = Quantity LC = Lot purchased According to Rogers, Rogers and Ribeiro (2004), the instant that the curve of the storage cost and the cost of action are equal; the total cost is minimized, thus representing the LEC. After this point, the total cost becomes increased because of the cost of storage, according to Illustration 1.

Total Cost Cost of application

Storage Cost LEC

Q

Source: Dias (2005) Fig. 1: Bend the economic lot purchase

According to Bastos and Lauria (2006), the batch of economic production or manufacturing is a certain amount decided by the Company to be manufactured, and can only be initiated the production of other lots after completion of the first. The plot, to be scaled, to quantify time and inputs to be spent on manufacturing. On this basis, any variation in the amount consumed is an anomaly that should be investigated, which enables better control over production.

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As Slack, Chambers and Johnston (2002), the calculation of economic lot of farming is based on the maximum level of stocks (M), slope stock being produced (PD) and total (C). Equation 6 describes how to calculate the LEP. LEP 

2C P. D C e (1  D / P)

(06)

Where: Cp: unit cost of the application; Ce: cost of maintaining inventory in the period, per unit; D: sued item, and P: production rate of the product. According to Moura (2000) the economic lot production uses similar concepts to the economic lot of hedging, but instead of using the order cost (purchase), the total cost for calculating the economic lot, it uses the cost of preparation, engineering terms relevant to the manufacturing process of the piece. According to Dias (2005), the system of inventory control function is to measure and monitor the stocks on which is a major issue and concern for administrators. It is a constant and growing entrepreneur to find formulas to reduce inventories without compromising the production process and without increasing costs. According to Martins and Atl (2002), using a system of inventory control leads to an improvement in productivity, tighter control of assets really important, flexible manufacturing environments, greater responsibility to lower levels with the consequent demand staff with higher education. According to Arnold (1999), the system point of order is a way to determine when to ask for material, because when the stock of a particular item reaches a predetermined amount, it gives new application. That is, the point of application is the amount of parts we have in stock, which ensures the production process that does not suffer problems of continuity, as we await the arrival of the consignment purchased during spare time. This means that when a certain inventory item reaches its reorder point, we complete the supply of stock, opening a purchase order (POZO, 2002). According to Dias (2005), the process of replacement of the stock should be started when the virtual inventory reaches a predetermined level, which is the point of application. As shown in Equation 10. PP  CxTR  E.Mn

(10)

Where: C = Average consumption TR = Time to Spare E.Mn = minimum stock According to Dias (2005) curve ABC is the method that has been most used because it allows the identification of items needing attention and appropriate treat149


ment as his administration, which is used for setting sales policies, establishment of priorities for the planning of production and a series of other problems common in the company. According to Dias (2005) after the items have been ordered by relative importance, the classes of the curve ABC can be defined in the following ways: – – –

Class A: group of the most important items that should be treated with special attention by the administration Class B: group of items in an intermediate situation, and Class C: group of less important items.

The use of the ABC curve becomes essentially beneficial, since it can reduce the assets in stock without sacrificing safety, since it controls more strictly items of class A, and more superficially, the class C The ABC classification is used for various units of measurement such as weight, length, volume, unit cost, etc. (POZO, 2002, p. 86). In Illustration 2, note that the items rated most important, are called "A" and which are about 20% only of the items of the product line of a company, representing about 70% of total sales. That is why we, the benefits of the efforts made to decrease the average inventory of these items are much higher when compared to the unspeakable benefit of the effort to reduce the average inventory of the items that make up the region of the curve C, which are treated less logistical importance in relation to other levels.

Fig. 2: Graph of the concept of ABC Source: Correa, Gianesi and Caon (2001).

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According to Daru and Lacerda (2005), a decision inherent in the positioning of the production is its policy of stock with respect to their finished items can be basically four types of produce to stock (Make-To-Stock - MTS), to produce custom ( MakeTo-Order - MTO), assemble to order (Assemble-To - Order - ATO) or custom design (Engineering-To-Order - ETO). Daru and Lacerda (2005) described that the MTS is a common practice, where one can forecast demand and can take time out of the crop to be produced, making better use of resources and the loading more evenly. But this policy has some disadvantages, which would be the high cost of storage and the difficulty of predicting what will be sold. According to Pacheco and Candide (2001), in MTS the product has started its production based on demand forecast. The arrival of the request causes your service almost immediately. It is suitable for products with predictable demand, and may have higher inventory costs. The customer has little direct involvement in product design (ARNOLD, 1999). According to Machado Neto (2003), the MTO production of the desired products only starts after the confirmation by the customer. Do you work with stocks of finished products. This technique is suitable for products with low demand, the forecast is very complex and have high cost of storage, i.e., perishable, and inadvisable to market products which have the speed factor of service as vital. The second MTO Arnold (1999) means that the manufacturer does not begin to manufacture the product until the customer order is received, i.e. the final product is standardized and made to order. On the ACT, the main components of a product are produced for inventory based on demand forecast. When the request arrives, it will be assembled product, using the components previously produced. It has the advantage of reducing the lead-time of service, since this is reduced to the time of final assembly. It is appropriate when a small group of components used to generate a large number of products, and a product differs from others in terms of inclusion or exchange of one or a few components, the parts that make up the final product is stored until the receipt of customer orders (BERTRAND; ZUIJDERWIJK; HEGG, 2000; PESSOTO, SOUZA, 2005). The strategy emphasizes the ETO phase of the project, which is usually developed only after receiving the request been approved by the client, giving early stages subsequent to the project. As a result, there is no stock before the arrival of the request, even during the design phase. The difficulty with this strategy is to implement controls on deadlines, quality and design in a dynamic environment of uncertainty and complexity (MACHADO NETO, 2003). According Pessoti and Souza (2005), the ETO system is characterized by being an extension of the MTO with the project being done almost entirely based on customer specifications and are only be started after its approval.

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According to Rodrigues (2008), the existence of the stocks in the ETO system, there may be as criticality design, characteristics of the productive sector and consumers because there may be a phase of simulation and product testing to observe the adherence to standards as defined in Illustration 3 shows the form of occurrence of stocks.

Fig. 3: Process Flow Engineering-To-Order company Source: Rodrigues (2008)

3 Planning and control of production According to Welzel (2002), planning and production control (CFP) determine the course of production, following the process, realigning what was planned and exerting their control. Inside the function "production" can be classified as management decisions in strategic (long term), tactical (medium term) and operational planning and control (short term) (DAVIS; AQUILANO; CHASE, 2001).These decisions will influence the form of plan, schedule and control the production (RUSSOMANO, 2000; Erdmann, 2000). A system of PCP enhances the efficient use of productive resources, providing smooth production, and has the function of managing customers' needs, based on industry sales, generating one or more orders of production services, minimizing delays, managing the utilization stocks and, therefore, better serve customers and, thus, managing and controlling the production (Salomon et al., 2002). Put simply, set the physical arrangement is to decide where to place all facilities, machinery, equipment and production personnel. The physical arrangement is

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one of the salient features of a productive operation because it determines the "shape" and appearance. For Stevenson (2001), the need to make a planning of the physical arises both during the design of new facilities as when revising existing plant projects. The most common reasons for the reformulation of the physical layout of projects are: (a) the inefficiency of operations (i.e. high cost, the existence of bottlenecks), (b) accidents, or risk to physical integrity and security (c) change in design, products and services, (d) introduction of new products or services, (e) changes in production volume or mix (composition), (f) changes in methods or equipment, (g ) changes in environmental or other, legal, and (h) problems related to staff morale (i.e., lack of face to face). According peinaldo and Graeml (2007) and Slack, Chambers and Johnston (2002) the need to make decisions about the physical arrangement is due to several factors, such as: (a) T HE expansion of productive capacity, (b) High operating cost (c) Introduction of new product line, and (d) improving the work environment. Even as peinaldo and Graeml (2007) define the basic principles of physical arrangements, as: (a) security, (b) economy of movement, (c) long-term flexibility, (d) the principle of progressivity, and (e) use of space. Slack, Chambers and Johnston (2002) classified into four basic types of layout: layout positional layout by process, product and layout-by-layout cell. This last mentioned is the layout that most influence in reducing waste from the perspective of philosophy of Lean Production. An explanation of each type of layout: (a) positional layout, (b) the layout process, (c) cell layout, and (d) layout for the product. According to Christopher (2009), Kanban system is a "pull" driven by demand from the next customer. The goal of this system would produce only the amount needed for immediate demand. The Kanban is seeking a balanced supply chain with minimum inventory at each stage and where the process and the quantities of material in transit and inventory are kept to a minimum. According to Severo Filho (2006), kanban is a tool to operation the just-in-time production, allowing transforming the production of "pushed" in "pull". The kanban is an important element of the Toyota Production System, a system that aims at total elimination of losses, however, is not synonymous, and the kanban technique to help implement these principles, as a system of self-control at the plant level. According Danni and Tubino (1997) Equation 12 scales the number of cards statically, without taking into account the lead time is dependent on the number of cards and the capacity of Container and does not consider other factors that may influence the operation of the kanban system, such as: the variability of processing times and demand, setup time, the frequency of broken machine, there are quality problems with products, etc.. K

D.LT C

(11)

153


Where: D = Demand LT = Lead time C = Capacity

4 Case Study The company studied was founded in 2000, aiming to meet the manufacturers, distributors and retail line of screws for bicycles and cars. It is a family business in which the CEO has decided to invest in the structure and organizational processes in order to reduce costs without having to promote layoffs. The company currently employs 20 professionals, which are distributed in the administrative sector and operational, has an area of 2,000 m 2 and 11 representatives who are located in major cities of Brazil. A major difficulty of the undertaking is the lack of planning for the management of the supply chain, by having very small items and delay in its production process is given the need to maintain an inventory so that it meets the demands of customers as as possible without delay. The company currently works with two categories of products, which are divided in the following scale; see Table 1 and Illustration 4: – –

Automotive: are special products for cars that have about 60 items in your production line. Bicycles: are special products for bikes that have about 75 items in your production line, which has no seasonality, being produced all year round with peak production from April to December.

Product Line

Number of models

Representativeness%

Automotive

60

44.4%

Bikes

75

55.6%

Tab. 1: Value number of models by product

Automotive Bikes

Fig. 4: Representativeness % in the number of models

The company has a policy of making to stock (MTS), as it does not have a well defined strategy regarding the management of the supply chain and for not having reliable suppliers. This policy mask errors in demand forecasts, inventory manage154


ment and even in production, because there is no way to immediately detect the production of a wrong product, an order canceled, etc., Drastically affecting the cost and performance. These costs are the result of lack of raw material for the production and hence the delay in the delivery of the finished product and can get to the point the client to cancel the request and in retaliation over a period of time without making requests. May also incur costs to maintain a stock of finished product in which the request was canceled. The lack of raw materials also affects the performance of the company as a whole, as there is the domino effect, in which production does not deliver on time the seller has to spend time negotiating new deadlines and administrative needs to negotiate with suppliers urgent replacements with different prices. The company has a management system which was not given due importance and therefore it was not retrofitted for the operation and there was no way of recovery on the feedback. The lack of control of stocks implies a weakness of the company as the direction is not to measure accurately the amount of capital invested in the operation. While the company studies as the system to function properly, or new deployment, staff training and definition of who is monitoring the feedback, the company decided to develop some spreadsheets in Excel in order to track their inventory costs and production .In order to try awareness direction and therefore the officials of the importance of keeping the system up to date. The company adopted the model of the physical arrangement of process or functional, organizing the equipment according to their production function, work in process was arranged to minimize the displacement of the raw material for processing between the processes thus avoiding the risk of accident and / or loss of time on transportation. The company has 5 presses of 120 t, 4 Roll Automatic thread cutting machines and 3 manuals. The waiting areas and finished goods in process and raw materials are located in a strategic way that will not disrupt the process flow of the company. The stock of raw material is in the production environment as a way to expedite the removal and return, as, for example, the coil of wire cannot be used in its entirety and it shall be returned to stock for is accounted for the amount used. The layout facilitates the production staff responsible for the equipment to identify products that should be worked out, since there is no control kanban card. After the product through the process of pressing and tapping, it is transported to an area near the zinc as a way to expedite the process, because it takes about 30 minutes. The Illustration 5 shows the entire route that follows the raw material in production.

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Fig. 5: Fitting physical production

For the production of a particular product the company uses the raw material 7.10 BTC course which goes through the following machines: Press 1 - has the capacity to produce 48 parts per minute, and passing through threaded manual that has the capacity to 30 parts per minute. The zinc coating of 20 kilos of this stuff lasts 30 minutes in a water bath and stopped rotating, after being packed in plastic bags with 25 pieces each. Illustration 6 shows the production process of automotive product screw.

Fig. 6: The production process of the company

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The quality testing of products is done every 100 parts of the test is a manual and visual, in which the operator makes an analysis of the product to see if it follows the rules of manufacturing, since if there is an error and not observed will generate the loss of the entire batch and consequently an increase in production costs. In Illustration 7 describes the training strategy adopted by the company stocks, which follows the model described by Rodrigues (2008), in Illustration 4. In this model the formation of stock occurs before and after the production process, in order to protect the production of market fluctuations, but this incurs some problems: (a) difficult to identify gaps; (b) high cost of stock, and (c) use of large areas that could serve the production.

Fig. 7: Process Flow MTS company

In Illustration 8 is presented the graph of the ABC classification of products, as Table 2 aiming to support the company's management in setting the production cycle. In the ABC classification adopted by the company can be seen that the products that comprise the class A is approximately 17.46% of all finished goods and have a financial leverage of approximately 80.66%. CLASS

VALUES%

GROSS%

A

80.66%

17.46%

B

15.32%

26.98%

C

4.02%

55.56%

amount

100%

100%

Tab. 2: Classification of ABC company

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Fig. 8: Summary of classification of products#

On this assumption the company should endeavor to better define the production cycles and volumes of stocks to allow for some raw material for such products. The company does not work with any kind of control of safety stock, minimum, average and maximum control is done visually, i.e., when the official responsible for the inventory notes that the volume is low it starts with a production order. Often this visual control failure causing a lack of product and even a surplus production, as there may be duplication of the production order, since the person you want your request is treated immediately. On this assumption it was decided to analyze and calculate the values of inventory control in order to reduce outages visual control and reduce costs and waste production. An equation 13, 14, 15 and 16 shows illustratively the form of how these calculations are made. ES  50 x0,20  10 80  10 EM   45 2 E max  10  80  90 E min  10  (10 * 0,95)  10,95  20

(13) (14) (15) (16)

The company is not an appropriate estimate of the LEC, as it manages to work this methodology from the knowledge gained since the founding of the company, i.e., this calculation works empirically, as needed and forecasts of possible demands.

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It may be noted that some products are purchased from suppliers and is stored for an indefinite period, thus generating a cost of storage, occupying spaces that could serve other projects. If the company switches to the LEC model which is described in Equation 1 may be taken to rationalize the purchase volume with their delivery schedule by the supplier, reducing the occurrence of lack of raw material. Equation 17 exemplifies the use of this model. LEC 

2.20000.3  219,0890  220 2,5

(17)

As with the LEC, the company works a lot with the knowledge of the production manager and operators, as they already have empirically how the equipment should produce and how much material is required in a work shift. This kind of empiricism can lead the company to take losses on management of in-process inventories, because there is no way to know immediately if the product is being done within the established rules, since the management is done visually. This can lead to inventory management to another problem, which is producing the same product in different batches absorbing a different amount of raw material. In Equation 18 is described in the form of calculation that can be adopted by the company. LEP 

108000 2.3.18000   211,1010  212 18000 2.4235 ) 2,5.(1  588000

(18)

The company has no supply contract, which included deadlines and late fees, which can generate a lack of raw material and consequently the possible loss of sale. Using the model as a point of order, you can monitor the level of reliability of the supplier to the company and also know more accurately the time to generate requests and when they should be being delivered to the company. Equation 19 exemplifies its use. PP  384.30  20  11540

(19)

The use of the identification system for Kanban production, the company adopts the philosophy of sending control chart handwriting and attached it to the production order. Why not be made any calculation of the number of cards needed for a production order, we can detect more than a weakness on the control of the lots. The use of the Kanban system with the LEP will allow control over what, when, as and when it is produced, the Kanban card may also allow the traceability 159


of all raw materials used in a particular product. In Equation 20 is a description on how to calculate the number of cards. K

18000.0,5  18 500

(20)

5 Conclusion The initial purpose of this study was to identify and organize the production processes of a company in the automotive parts industry, which has flaws in the management of the supply chain. To obtain the data from this study, we used several sources including semi-structured, in-situ observation and document analysis. Therefore, with the information obtained from the company could evaluate some changes to be implemented to the best fit in your production process. Without any kind of inventory control of raw materials in process and finished product the company may have had low-volume production, high inventory costs and therefore higher financial costs. With the reorganization of the supply chain of the company facilitated the identification of several problems, and thus addresses the key questions as: what, how, how much and when to produce. The whole system of business should be reorganized into consideration the information necessary for adequate control, and defined the responsibilities for this feedback process that is always updated. With the ABC classification could observe the items that need attention by the company, and the materials that did not exit, in which only entailed high costs for its maintenance. Just as the ABC classification to identify and define the safety stocks, which is a protection so that does not lack of material as well as stocks average, maximum and minimum, so as to assess the amount necessary to avoid an absence of matter raw and without any accumulation in inventory. In the production process of the company responsible for the sector performed a quality test of the product in 100 parts, it was suggested that this test will be conducted early in the production process and is performed every 100 pieces, so they can be detected the errors in first items. The physical arrangement of the company is organized functionally to facilitate the process, but as it adopts the MTS process was established calculations LEC and LEP, you do not have a high accumulation of its raw materials and the manufacturing of the items is done at the right time, so there is never any cost to remain high in stock. With these calculations, the company may make delivery schedules of raw materials for its suppliers, setting deadlines and penalties in case of delay by the supplier, thereby avoid possible loss of orders.

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The company is adopting the kanban system for production so that facilitates the identification of products and maintaining a traceability of the production process of a private product; they have a guarantee that the process will not be problem. It is recommended that the company use these formulas to find a balance of stocks and improve from them, in order to have a solid idea about the current situation of the company. Through the proposal concluded that the stock of raw material and finished product can be significantly reduced without the occurrence of late buying, production and distribution of products. It is suggested that the company make the deployment of an ERP system that allows the largest operation of the supply chain. So the company makes networking and all sectors of the company to work with greater flexibility and better results in decision-making. Finally, there is the possibility of implementation of the proposal obtained from this work together with the complementary actions suggested here, in order to make it more efficient and effective.

References Arnold, J. R. T. (1999) Materials Management: An Introduction. 1. ed. São Paulo: Atlas. Bastos, A. P.; Lauria, R. L. (2006) Optimizing the Design of Batch Production of the Restricted Area Storage. In: XXVI Encontro Nacional de Engenharia de produção, 2006, Fortaleza. Anais... Fortaleza: Enegep, 1 CD-ROM. Bertrand, J. W. M.; Zuijderwijk, M.; Hegge, H. M. H. (2000) Using hierarquical pseudo bills of material for customer order acceptance and optimal material replenishment in assemble to order manufacturing of no modular products. International Journal of Production Economics, n. 66, p.171-184. Castro, R. L. (2005) Planning and control of production and inventory: a survey of Brazilian automotive supply chain. Dissertação (Mestrado em Engenharia de Produção). São Paulo: POLI/USP. Christopher, M. (2009) Logistics and supply chain management: creating networks that add value. 2. ed. São Paulo: Cengage Learning. Corrêa, H. L.; Gianesi, I. G. N.; Caon, M. (2001) Planning, scheduling and production control: MRP II / ERP, concepts, use and deployment. 4 ed. São Paulo: Atlas. Danni, T. S.; Tubino, D. F. (1997) Dynamic adjustment of the number of kanbans in a JIT production system through simulation. In: XVII Encontro Nacional de Engenharia de produção, 1997, Gramado. Anais... Gramado: Enegep, 1 CD-ROM Darú, G. H.; Lacerda, V. C. (2005) Using Dynamic Programming for Multirotulada Balancing the Use of Tool. In: Congresso Nacional de Matematica Aplicada e Computacional, 28., 2005, São Paulo. Anais... São Paulo: SENAC. Davis, M. M.; Aquilano, N. J.; Chase, R. B. (2001) Fundamentals of production management. 3. ed. Porto Alegre: Bookman Editora. Dias, M. A. P. (2005) Materials Management: principles, concepts and management. 5. ed. São Paulo: Atlas. Erdmann, R. H. (2000) Production planning and control. Florianópolis: Papalivros. Francischini, P. G.; Gurgel, F. A. (2002) Materials Management and property. São Paulo: Atlas.

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Nicolle da Silva Panzuto and Paulo Cesar Chagas Rodrigues Godinho Filho, M. (2004) Paradigms of strategic manufacturing management: configuration,

relations with the planning and production control and exploratory study in the footwear industry. Tese (Doutorado em Engenharia de Produção). São Carlos: UFSCAR. Machado Neto, R. G. (2003) Lot sizing production, storage and transportation along a general multistage supply chain, subject to constraints of production capacity. Dissertação (Mestrado em Engenharia deProdução). Curitiba: PUC/PR. Martins, P. G; Alt, P. R. C. (2002) Materials Management and heritage resources. São Paulo: Saraiva. Moura, D. A. (2000) Characterization and analysis of a collection system programmed parts, "Milk Run" in the domestic auto industry. Dissertação (Mestrado em Engenharia). São Paulo: POLI/USP. Pacheco, R. F.; Cândido, M. A. B. (2001) Methodology for assessing the feasibility of changing the management strategy of the demand for MTO to ATO. Unpublished. PUCPR. Peinado, J.; Graeml, A. R. (2007) Production management: industrial operations and services. Curitiba: Unicenp. PessotI, H. R.; Souza, F. B. (2005) Analysis of the impacts of migration from one system to an MTS system in ATO manufacturing strategy and a competitive furniture industry. In: Simpósio de Engenharia de Produção, 12., 2005, Bauru. Anais... Bauru: FEB/UNESP. Pozo, H. (2002) Management of material resources and heritage: a logistics approach. 2. ed. São Paulo: Atlas. Rodrigues, P. C. C. (2008) The inventory management in production systems EngineeringTo-Order and Make-To-Stock: case studies on companies in the graphics sector. Dissertação (Mestrado em Engenharia de produção), Bauru: FEB/UNESP. Rogers, P.; Ribeiro, K. C. S.; Rogers, D. (2004) Assessing the risk in the financial management of inventories. In: Simposio de Administração da Produção, Logística e Opreações Internacionais, São Paulo. Anais… São Paulo: FGV, 1 CD-ROM. Russomano, V. H. (2000) PCP: Planning and Production Control. 6 ed. São Paulo: Pioneira. Salomon, V. A. P. Contador, J. L.; MARINS, F. A. S.; SANTORO, M. C. (2002) Potential costs of production and benefits of Planning and Production Control. In: ENCONTRO NACIONAL DE ENGENHARIA DE PRODUÇÃO, 22., Curitiba. Anais...Curitiba: ABEPRO. 1 CD-ROM. SEVERO FILHO, J. (2006) Integrated logistics management: materials, PCP and marketing. 2 ed. Rio de Janeiro: E-papers. SLACK, N.; CHAMBERS, S.; JOHNSTON, R. (2002) Production management. 2. ed. São Paulo: Atlas. STEVENSON, W. J. (2001) Management of production operations. 6 ed. Rio de Janeiro: LTC. WELZEL, E. (2002) Electronic commerce and industry: a case study of Cremer S.A. In: SIMPÓSIO DE ADMINISTRAÇÃO DA PRODUÇÃO, LOGÍSTICA E OPERAÇÕES INTERNACIONAIS, 5., São Paulo. Anais… São Paulo: FGV, 1 CD-ROM.

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III. Optimization Methods in Transportation Processes

163

Intermodal Transportation

Katharina Grobleben

Abstract Intermodal freight transport has become an emerging research field and popular topic in the recent past. Catalyzing this development, four dynamics can be identified. First, intermodal transport is seen as an alternative and competing mode to uni-modal road transport. Further, due to rising environmental concerns from growing emissions of the transport sector, intermodality has become an important point on the agenda of national and supra-national policy makers. Nationwide and European wide, there have been efforts to spur a modal shift from road to alternative modes of transport. Further, an industry centered around intermodal transport, such as services and equipment, has emerged. According to the European Environmental Agency (EEA), transport industry increased its energy consumption by 33% between 1990 and 2006. However, meanwhile technology innovations improved vehicles emission intensities, resulting in a reduction of 37 % between 1990 and 2007 for the EU-27 states (EEA, 2009). Nonetheless, despite successful efforts in improving fuel efficiency of vehicles, growth in demand for transport and the high correlation of energy consumption and greenhouse gas emissions, fosters the need for alternative, low energy consuming transportation. According to the Statistical Pocketbook by the European Communities for Energy of 2009, 45.6 % of total EU freight was carried by road, 10.7 % by rail , 3.3 % by inland waterways and 3.0 % by oil pipelines. Contrary to the efforts of White Paper of 2001 by the European Council, a balancing of transport modes and shift has not been effectively realized so far. In order to achieve a modal shift, alternative freight transport modes have to be able to effectively compete with road transportation. Mode choice is most often decided by shippers or freight forwarders. Hence, alternative transport modes have to meet shipper's requirements as mode choice depends on their decision making. Therefore, the author has developed a framework, which identifies and ranks decision criteria of shippers for freight modes and employes these in a performance measurement framework for assessing the competitiveness of two intermodal transport solutions in comparison with uni-modal road transport. Thereby, the model is based on a combination of theoretical and empirical analysis of freight mode choice. In addition, performance measurement is conducted by assessing intermodal transportation using indicators, which have been mutually developed with focal firms and have been based on empirical social science and operations man165

Katharina Grobleben

agement theories. With this model, the author is, by her best knowledge of current research, filling a gap in the emerging research field of intermodal freight transportation. This model contributes to EU‘s efforts to foster intermodal freight transport by providing a framework to assess intermodal freight transport performance across European countries, while simultaneously incorporating decision criteria, which enable to better position intermodal freight transport as an alternative to road transport.

Keywords: Intermodal freight transportation; Freight mode choice; Performance measurement; European Union

1 Introduction Transportation is an important sector of the European economy. Hence, the European Union (EU) and national policy makers likewise have strong political interest to secure a steady growth of the transport sector. Along with previous European policy implications, the White Paper of 2001 aims at a modal shift and thereby responds to present and rising challenges such as the predicted doubling of traffic by 2020, dependence on increasing oil prices and rising congestion of roads in order to decrease the number of traffic accidents as well as limit steadily rising carbon emissions. Along with stricter environ mental regulations by supra-national agreements such as the Kyoto Protocol, a change in the transport sector is sought. In this respect, intermodal transportation, the combination of alternative, environmental friendlier modes of transport on the long haul with road transport on the short leg, is a promising option [14]. However, despite considerable efforts by policy makers and operators to foster a modal shift in European freight transport towards intermodal transportation, no significant change can be currently observed [34, 13]. On the basis of a review of macro-economical motives by EU policy makers, an operational perspective is taken in order to provide the opportunity to better understand the discrepancies between political motives and operational practice.

2 Macroeconomical Stimulus for the Implementation of Sustainable Transportation „Transport infrastructure is fundamental for the mobility of the persons and goods and for the territorial cohesion of the European Union “as the backbone of international and intra-community trade [17]. Meanwhile, the transport and logistics sector provides more than 8.9 million jobs [11, 16]. Accordingly, the EU‘s efforts for change in the transport sector are catalyzed by a variety of concerns and drivers. On the one hand, there are strong political interests to further liberalization of the sector and to increase trade and commercial community exchange in order to 166


strengthen the community economically and politically in the global arena. On the other hand, ecological and socioeconomic issues are considered. Shifting freight transport towards alternative modes will decrease rising congestion and accidents on European roads. Although technological improvements of vehicles have increased over the years, the number of accidents involving personal injuries has nearly remained at the same level [4]. Economic growth and community cohesion can be achieved in a sustainable way with common effort by advancing the transport infrastructure and promoting sustainable flow of goods. Also, the quality and efficiency of current and future inter community cargo traffic, especially through the increased accessibility of countries in Eastern Europe, can be achieved by fully utilizing the existing capacities and expanding the usage of the different modes of transport. Present limitations caused by great congestions on transEuropean roads can be unlocked and thereby foster a successive enlargement and leverage of the trade potential between and within EU Member States. Limiting the negative effects of increasing traffic, while simultaneously promoting greater trade and employment opportunities, the development of a sustainable transportation model is sought. To this end, the EU’s main objective is to further increase intermodal freight transportation [17].

3 Environmental Drivers for Intermodal Transportation The advantages of intermodal transportation are three-pronged: balancing transport modes is key to protect the environment. As illustrated in Figure 1, no significant change can be identified despite EU and national policy making supporting a modal shift in freight transportation [11].

Fig. 1: Modal Split 1995-2007

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Katharina Grobleben

However, the capacity and energy efficiency of alternative transport modes are considerable. To compare, a truck can approximately carry 40 tons, whereas a European barge can load around 1350 tons [23]. Meanwhile it is one of the lowest polluting modes of transportation [1]. Consequently, a shift towards more fuel efficient modes of transport, such as inland waterways or railway contributes to lower car bon emission and decrease of the dependence on rising oil prices. More than 28% of all emissions of carbon in the EU stem from transportation, 84% of these emissions result from road transport only. According to the European Environmental Agency (EEA), transport industry increased its energy consumption by 33% between 1990 and 2006. Technology innovations improved vehicles emission intensities, resulting in a reduction of 37 % between 1990 and 2007 for the EU-27 states [2]. Nonetheless, despite successful eﬀorts in improving fuel eﬃciency of vehicles, growth in demand for transport and the high correlation of energy consumption and greenhouse gas emissions, foster the need for alternative, low energy consuming transportation [16, 19]. In order to meet future over-all greenhouse gas emissions targets by 2020, the transport sector needs to change considerably. Research shows that „the fuel consumption per ton-km of transported cargo by inland waterways is one-sixth of that of road transport and half that of rail transport“ . Also, environmental noise is decreased, which in particular stems from motor vehicles.1

4 Performance Measurements In light of the almost unchanged modal split in European freight transport and simultaneous pressure by policy makers to reduce emissions and energy usage to increase sustainability and long-lasting existence of the transport sector, service requirements by businesses have to be met in order to increase alternative mode employment in current logistics operations [39]. This how ever can only be achieved if demand and supply characteristics by businesses and operators can be adequately met. Based on an extensive literature review on intermodal transport research, no comprehensive performance measurement could be found comparing actual intermodal freight transport performance with uni-modal road transportation. Although the [32] has identified the need for a holistic approach of benchmarking incorporating rail, road and sea transport, the author did not find an adequate performance measurement for inland waterway transportation, nor a comparable study of more than two modes. In the following, a theoretical background of existing performance measurement methodologies will be presented leading to a presentation of an intermodal freight transport performance measurement framework with the overall aim to improve intermodal freight transport operations in the long-term through adequate monitoring of performance.

168


4.1 Theoretical Background Literature on performance measurements can be assigned generally to two different categories - namely those providing recommendations for selecting appropriate performance measurement methods and those on the criteria to develop adequate measures. Thereby, performance measurement fulfils not only a measurement function but also an evaluation one of the achieved performance [37]. To adequately measure and evaluate performance in a holistic approach, measures should take an internal, micro-economical as well as external customer-oriented perspective.

4.1.1 Internal, Micro-economical Perspective In regard to internal performance measurement, companies have mostly focused on financial indicators in the past. Typically such measures are objective, accurate as well as easy and inexpensive to collect [10]. From a resource perspective, costs are critical to the organization. However basing performance measurement entirely on financial indicators offers several downfalls. The documentation of costs by businesses may present lack of relevance of cost categories, cost distortions and inflexibility as well as performance is mostly measured using historical data [30]. Hence, also non-financial indicators and non-numerical measures should be considered to evaluate and measure the performance of transportation and supply chains [7, 24]. How ever, these “soft” indicators are more difficult to gather, measure and compare [27]. The OECED has summarized and analyzed benchmarks of EU member states providing a framework to improve system performance in intermodal transport operations [32]. Despite the acknowledgement of soft and hard indicators being relevant for sufficient performance measurement, the presented summary of national benchmarking of selected countries does not measure soft indicators [32]. Moreover, performance indicators and measures are to great extent domain specific [27]. Although logistics services have changed over time moving from basic transport towards more sophisticated logistics services, performance of freight transport is still mostly evaluated using the same indicators [5]. How ever, the definition of performance in evaluation of freight transport performance goes beyond a mere look at the statistical development. Accordingly, an increase of road haulage in freight transport should not be misread with road haulage being more efficient, but rather acknowledge that the measurement depends on the definition of performance.

4.1.2 External, Customer-oriented Perspective According to the Intermodal Freight Transportation Advisory Group of the OECD, performance measurement poses considerable hurdles for intermodal transport benchmarking due to restrictions on data availability and differences in measurement of input and output factors [32]. Different stakeholders within the intermodal 169

Katharina Grobleben

transport chain have varying interests, which influence the set of performance indicators employed in benchmarking. In order to move beyond mere measurement of financial and traditional productivity factors, service quality of logistics operators have to be assessed as well [5]. Thus, a multi-criteria framework has to be employed to capture also the economic, service perspective of a logistics firm’s operations [5]. As intermodal transport is based on the combination of different modes, the performance of intermodal freight transport operations should acknowledge these different types of freight transport services, which inherently re quire different usage and types of performance indicators. In this respect,[5] found that performance indicators correlate with the production systems incorporated by the demand side. Accordingly, in order to identify adequate performance indicators, they identified three production systems, namely industrial production and circulation characterized by large-scale standardized flows of goods using different modes of transport including rail and barge, products determined by final demand, characterized by the employment of different logistic and transportation strategies based on consolidation of flows, JIT deliveries, service quality and adaptation to demand variations and production system of the industrial, flexible and professional type which produces products of competencies, user-producer interactions and services, which cannot be standardized or scaled, and thus are consolidated to small shipments, which are sometimes carried out by the production firm itself [5]. Accordingly, an adequate performance measurement framework has to acknowledge which production system the transport modes are serving to.

4.2 Performance Measurement in Logistics Within the research field of supply chain performance in transport logistics, the definition of logistics performance is widely discussed. According to Gleason and Barnum, logistic performance embraces effectiveness as „the ex tent to which an objective has been achieved“ and efficiency as „the degree to which resources have been used economically“ [20]. This distinction has been shared widely across the supply chain management community [26, 9]. Hence, to measure supply chain performance efficiency and effectiveness should be considered when seeking adequate indicators.

4.2.1 Logistic services There is much discussion on what constitutes a logistics product, which is ultimately the subject of performance measurement. [36] have argued that the „seven right conditions“ for the logistic service are product, quantity, time, condition, customer, place and cost. [29] however limited the key categories of a logistic service providers to customer, resource and finance. [8] did the same limitation but on time, dis170


tance and money. [15] argues for the categories finance, quality and resource. However, one of the most commonly used categorization is by [31] emphasizing quality, time, flexibility and costs. The latter on will be employed in the measurement framework of intermodal transportation.

Tab. 1: Measurement frameworks

4.2.2 Classification of Measures Measures can be distinguished between those aiming at clarifying performance levels within an individual firm and measures taking into consideration the entire supply chain perspective aiming at an optimization of inter organizational performance. The first distinction implies measures of performance from an internal or intra-firm perspective, whereas the latter one focuses on an inter-firm perspective. Within the perspective of internal performance measures there are several researchers who developed categories. [15] distinguished between performance indicators „what you are doing“ - and diagnostic indicators- „why a process is not performing as expected“. [7] differentiated between engineered/operational and financial indicators. [18] classified performance measures into input and output indicators to better represent the value chain within a firm, as each activity performed includes the transformation of in puts into outputs. [33] identified qualitative and quantitative performance measures. For the purpose of the comparative performance measurement framework aimed to be developed in this paper, English et al.‘s view is favored based on the ability to not only measure but also evaluate the achieved performance as the categorization distinguishes metrics into a performance category and a diagnostic category, which allows a subsequently analysis of issues for improvement of intermodal transportation.

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4.2.3 Performance Measurement Models Despite the vast number of metrics, no general accepted framework for supply chain performance measurement exists. [8] observed that „[i]n the logistics literature, more attention has been placed on individual measures than on systems of measures” [8]. Nonetheless, a few models have been developed in the past two decades. In 1998, [40] proposed a model focusing on the corporate level of integration in the supply chain and strategy. [3] developed a performance evaluation framework for manufacturing firms, in which three perspectives, namely resources, output, and flexibility are key elements to the measurement process. In 2001, [35] presented a framework to benchmark supply chain performance within a firm. [22] developed a supply chain performance model to evaluate performance achieved at three management levels. Nonetheless, all the above presented performance measurement models lack agreement of goals and performance measures in the supply chain activities

Tab. 2: Measurement frameworks

Hence, it is useful in system analysis to develop focus when seeking an ad equate performance measurement system [3]. [8] identified an inconsistency and overload of measures used in performance measurement. Further they found, that even in cases where metrics are examined for selection purpose, they are usually examined individually but not in the context of the entire supply chain and thereby lead to duplications, mistakes and redundancies [8]. Thus, in order to find a promising measurement system they formulate a few evaluation criteria for performance measurement systems for the transportation industry, namely to be comprehensive, casually oriented, vertically integrated, horizontally integrated, internally comparable and useful. In the following an overview of evaluation criteria will be given.

172


Tab. 3: Overview of evaluation criteria for measures

In the following, the evaluation criteria formulated by Caplice and Sheffi in 1995 will be further discussed as these criteria formed the basis for an adequate performance measurement model selection. Firstly, measures should be comprehensive, namely that they should take a holistic, multi-perspective. This implies that also non-financial measures should be included, which may drive financial results but are of more qualitative nature. Secondly, measures have to be casually-oriented in order to provide the diagnostic dimension to improve processes. Thirdly, performance measurement systems should be vertically integrated, meaning that measures should be aligned with the firm‘s overall strategy. As[6] found the extent and type of performance measurement likely to vary according to strategic orientation, it is important to align also lower level performance measurement systems with the firm‘s overall strategic goals. Fourthly, measurement systems should be horizontally integrated along a process rather than along each function or department as the absence of such horizontal integration may lead to lower coordination and cooperation across functions and departments. A literature review of currently available systems brought attention to two frameworks, which meet the four principles for measuring systems in transportation logistics.

Tab. 4: Evaluation of the various measurement systems of supply chain

As illustrated in Table 2, two measurement frameworks exhibit a compliance with all four requirements. Accordingly, in the following a brief discussion will highlight the two main frameworks‘ strengths and weaknesses. The first system is based on the commonly referred performance measurement model by [25], the „balanced scorecard“, which has been adjusted to the needs of transportation logistics by [7]. The other model is developed by the Supply-Chain Council and most commonly used for performance measurements in transportation logistics. Independently from a specific industry domain, [25] developed a performance measurement system 173

Katharina Grobleben

with the primary aim to gain better insight into business operations of a company. With their „balanced scorecard“, Kaplan and Norton proposed a way to measure outcomes in the field of a firm‘s finances, customers, internal business, innovation and learning. However, by their nature, performance indicators and measures are to a great extent domain-specific [27]. Therefore, [7] modified the „balanced scorecard“ to be utilized for the field of transportation logistics. [7] argued that despite the fact that the „balanced scorecard“ and supply chain management is most times independently studied and focused on, utilization of the „balanced scorecard“ may enable a firm to „leverage their supply chains into a source of competitive advantage“ [7]. As the name of the framework already suggests, the „balanced scorecard“ seeks to provide a „balance“ between non-financial and financial measures with short-term and long-term horizons. [7] identified waste reduction and enhanced supply chain performances as the key areas to focus on in the performance measurement of supply chains. In order to achieve such goals, so called „functional silos“ within the organization need to be eliminated while collaboration and coordination of marketing, production, procurement, sales and logistics have to be established. Essentially, they see the key to achieve better performance of a firm‘s supply chain in focusing on reducing waste, time, unit costs and enhancing flexibility response. In order to achieve these goals, the „balanced scorecard“ was adjusted to the specific needs of measurement of the performance of supply chains. The most significant change from the original framework by Kaplan and Norton to Brewer and Speh‘s „balanced scorecard“ hereby is that performance and diagnostic measures are incorporated. Although the original „balanced score card“ by Kaplan and Norton has received wide recognition within strategic management practices, it is hardly ever used in supply chain management practices [7]. The fact that Brewer and Speh seek to promote this framework by adopting its approach to more specific needs of supply chain management is encouraging, but does not eliminate the reasons for this industry wide inattention of it. Despite their adoption, the variety of measures are not reduced [8] to a few critical but essential ones, but rather suggest a number of types of metrics, that would fit under the original „balanced scorecard“. Accordingly, the adjusted “balance scorecard” does not provide practical focus. The second and most commonly used framework, the so-called „SupplyChain Operations Reference (SCOR) model“, has been developed by the Supply Chain Council. This model embraces supply chain management with both - a broad (multi-functional) as well as deep (multi-level) perspective. It identifies five different processes important to a supply chain, namely to plan, source, make, deliver and return. Although it means to include such activities as purchasing, inbound and outbound logistics and production/operation [12], the framework is not attempting to include each and every single step of it. More, it excludes activities such as sales and marketing, product development and research and development in the performance measurement framework. Thereby, focus on a few, most essential activities within a sup ply chain but also attention to the resource utilization of the focal firm 174


and its service effectiveness of the customers and suppliers involved are created. Therefore, this measurement model does enable the best indication as to how effective different transport options plan, source, make and deliver in the transportation logistics context [28].

5 Outlook In this respect comparative performance measurement of intermodal freight transport and uni-modal road transport along a selected transport corridor will be conducted [21]. Thereby the „Supply-Chain Operations Reference (SCOR) model“ will be employed to measure the performance of three different modes of freight transportation. Most relevant attributes of freight services derived from an interview series with stakeholders of three different industries will be used in order to cross-check the relevance of the employed indicators in the model. Thereby an identified lack of current performance measurement of intermodal transportation will be actively filled and will offer the basis for improved, realistic freight choice modeling.

References [1] European Environment Agency. Climate for a transport change - term 2007: indica tors tracking transport and environment in the european union. Technical Report 1, Office for Official Publications of the European Communities, 2008. [2] Andreas Barkman, Francois Dejean, and Kampel Elisabeth;. Greenhouse gas emission trends and projections in europe 2009 - tracking progress towards kyoto targets. EEA Report 9, European Environmental Agency, 2009. [3] Benita M.; Beamon. Measuing supply chain performance. International Journal of Operations & Production Management, 19(3):275–292, 1999. [4] Dag Björnland. Transportation planning as an effective tool for sustainable mobility. Marine Pollution Bulletin, 29(6-12):393–397, 1994. [5] Corinne Blanquart and Antje Burmeister transport: a service approach. European Transport Research Review, 1(3):135–145, October 2009. [6] Patricia J.; Bowersox, Donald J.; Daugherty. Logistics leadership - logistics organi zations of the future. Logistics Information Management, 5(1), 1992. [7] T. Brewer, P.; Speh. Using the balanced scorecard to measure supply chain perfor mance. Journal of Business Logistics, 21(1):75–93, 2000. [8] Y. Caplice, C.; Sheffi. A review and evaluation of logistics metrics Journal of Logistics Management, 5(2):11–28, 1994. [9] Joseph L. Cavinato. A general methodology for determining a fit between supply chain logistics. International Journal of Physical Distribution & Logistics, 29(3):162– 181, 1999. [10] Trevor D.; Henriksson Lennart E. Chow, Garland; Heaver. Logistics performance: Definition and measurement. International Journal of Physical Distribution & Logis tics, 24(1):17–28, 1994. [11] European Communities. EU energy and transport in figures. Technical report, Eu ropean Commission, 2009. [12] Supply Chain Council. Supply-chain reference model, 2004.

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Katharina Grobleben [13] Steven; Van Herbruggen Bart De Ceuster, Griet ; Logghe. Indicator assessment of the white paper on transport. Association for European Transport and contributors, 2006. [15] A.; Watson J.; English, J.R.; Mendoza. Quality monitoring of logistics systems. Draft publication, 64(1):12–40, 1999. [16] European Commission. A sustainable future for transport -towards an integrated, technologyled and user-friendly system. Technical report, Luxembourg: Publications Office of the European Union, 2009. [17] European Commission. Transport: What do we want to achieve?, May 2009. [18] Leonard; Fortuin. A survey of literature on reordering of stock items for production inventories. International Journal of Production Economics, 15(1):87–105, 1977. [19] Peder Gabrielsen. Assessing progress in environmental integration - freight transport demand (version 2). Technical report, European Environmental Agency, April 2009. [20] Darold T. Gleason, John M.; Barnum. Toward valid measures of public sector produc tivity: Performance measures in urban transit. Management Science, 28(4):379–386, April 1982. [21] A. Gunasekarana, C. Patelb, and Ronald E. McGaugheyc. A framework for supply chain performance measurement. International Journal of Production Economics, 87:333–347, 2004. [22] C.; Tirtiroglu E.; Gunasekarana, A.; Patel. Performance measures and metrics in a supply chain environment. International Journal of Operations & Production Man¬agement, 21(1/2):71–87, 2001. [23] Anja; Guse. Ausbau der Elbe muss weitergehen, September 2009. [24] David F. Ittner, Christopher D.; Larcker. Coming up short on nonfinancial perfor mance measurement. Harvard Business Review, November 2003. [25] David P.; Kaplan, Robert S.; Norton. The balanced scorecard-measures that drive performance. Harvard Business Review, pages 71–79, January-February 1992. [26] Philip B.; Tanner Ray D. Kleinsorge, Ilene K.; Senary nership: A new tool for performance evaluation. Journal of Business Logisticsr, 12(2):35–57, 1991. [27] Hans; Schut Martijn; Popova Viara; Krauth, Elfriede; Moonen. Performance mea surement and control in logistics service providing. Artifical Intelligience and Decision Support Systes, 2005. [28] T.C.E.; Lai, Kee-hung; Cheng. Supply chain performance in transport logistics: An assessment by service providers. International Journal of Logistics, 2003. [29] Kevin; Lockamy, Archie; McCormack chain performance. International Journal of Operations & Production Management, 24(12):1192–1218, 2004. [30] Brian H. Maskell. Performance measurement for world class manufacturing: A model for American companies. Productivity Pr Inc, 1991. [31] John; Platts Ken; Richards Huw; Gregory Mike; Bourne Mike; Kennerley Mike; Neely, Andy; Mills. Performance measurement design: developing and testing a process¬based approach. International Journal of Operations & Production Management, 20(10):119–1145, 2000. [32] OECD. Benchmarking intermodal freight transport. Technical Report 6, OECD, 2002. [33] Carlo; Rafele. Logistics service measurement: a reference framework Manufacturing Technology Mangement, 15(3):280–290, 2004. [34] Eva Savelsberg. Case studies-part ii: Innovations to improve the intermodal transport chain. In Innovation in European Freight Transportation. Springer Berlin Heidelberg, 2008. [35] Nitin; Shah, Janat; Singh. Benchmarking internal supply chain performance: De velopment of a framework. The Journal of Supply Chain Management, 37(1):37–47, April 2001. [36] R.D. Shapiro and J.L. Heskett. Logistics Strategy: Cases and Concepts. West Pub lishing Company, 1984. [37] J. Will M.; Stoop, Paul P. M.; Bertrand. Performance prediction and diagnosis in two production departments. Integrating Manufacturing Systems, 8(2):103–109, 1997.

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Intermodal Transportation [38] Vijay R.; Handfield Robert B.; Ghosh Soumen; Tan, Keah-Choon; Kannan. Supply chain management: an empirical study of its impact on performance. International Journal of Operations & Production Management, 19(10):1034–1052, 1999. [39] Marco; Torbianelli, Vittorio A.; Mazzarino. Optimal Logistics Networks: the Case of Italian Exports to Russia. Transit Studies Review, 16:918–935, December 2009. [40] Remko I. van Hoek. "measuring the unmeasurable"-measuring and improving per formance in the supply chain. Supply Chain Management: An International Journal, 3(4):187–192, 1998.

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Programming Tools, an Alternative to Optimize the Logistics at the Transportation Process of the Oil Palm Fresh Fruit Bunches (FFB)

Carlos A. Fontanilla, Wilson Adarme, Martin D. Arango

Abstract It was made a bibliographic search about the using of optimization models applied to the Colombian oil palm supply chain. As one result, only few publications, based on operations research techniques, were found. As well, in this paper it was used a Mixed Integer Programming (MIP) model, fed with simulation data. It allowed to optimize the logistics transportation process of the oil palm fresh fruit bunches (FFB), from the field to the oil palm mill and to minimize the transportation costs.

Keywords: Mixed Integer Programming, cost reduction.

1 Introduction At the Colombian palm oil industry, there are different equipments and frames used for the transportation of the Fresh Fruit Bunches (FFB), from the field to the mill. Prominent among them there are: auoto-loading (Jerez y Amézquita, 2004), that unload the empty containers and upload the FFB fully containers at the stockpiling centers to bring them to the mill; lorries that are filled by the unloading of FBB meshes, using lifting arms vehicles (this system requires that the lorry and the hydraulic arm vehicle visit a lot of collection points before the lorry capacity is reached); tractors and 3 to 5 ton capacity trailers (Fontanilla, et al., 2010); and cable way systems (Fontanilla y Castiblanco, 2009) for the FFB meshes transportation from the field to the mill. Despite the diversity of logistics schemes that can be used for the operation of the different systems of FFB transportation, theirs management is not centralized and there is a lack of coordination for the vehicles arrival to the mill. At high production season is common the lorries queues at the mill´s storage deposit, but at the lower production season it can be un supply of FFB at the mill, which means it must stop the processing. 179

Carlos A. Fontanilla, Wilson Adarme, Martin D.Arango

The absence of synchronization, does not only affect the processing operations, but impact on the transportation activities: it cause down times for transporters that arrive to the stockpiling center before the FFB is available, or loss of FFB quality when they arrive few hours later. In addition, the unavailability of the tools required for the FFB evacuation (meshes and containers, among others), that in most cases are provided by the collection vehicles, causes the diminishing on labor performance, extra costs due to the non opportune use of the technologies assigned to the process, FFB weight and quality losses, among others. Those disadvantages occur most often when the mill server several FFB suppliers, because they use different providers for the transportation services, with whom there is no control or coordination of schedules for the receipt of FFB. In term of cost, the transportation of FFB is the 5% of the share on the final production cost of the Crude Palm Oil (CPO), moreover, the harvesting and the milling are 16% and 21% of the share, respectively (Lans and Mil Corporation – LMC, 2008; Duarte y Guterman, 2009). Even when the participation of transportation cost on the production costs of a CPO is small, it is very important to avoid delays among the FFB cutting and their processing. The oil quality is deteriorated with the increasing of the time before sterilization because of its perishable product condition, once FFB are cut, theirs acidification process (Free Fatty acids – FFA, conversion) become faster. It is worth to say that the difference, in terms of price, among an optimal quality and a low quality oil, is up to the 5%, which implies a difference of US20-25 per palm oil ton (Corley and Law, 2001). This means that most of the effort and resources invested in obtaining a ton of palm oil, may be lost if there is no proper post-harvesting of FFB. On the other hand, the area planted with oil palm in Colombia has been growing at an annual rate of 10,2%, from 150399 hectares in 1999 to 360537 in 2009, at the same time as, the number of Crude Palm Oil mills increased from 51 to 53 (Fedepalma, 2001; Fedepalma, 2009; and Fedepalma, 2010). That is, while in 2000 an average of 3,000 hectares was assigned to a processing plant, in 2009 that number amounted to 6,000 hectares. The difference of the planted area averages assigned to a mill, suggests: not only an increase of the utilization factor over the installed capacity of the mills, and their approach to economies of scale, but also, larger distances to transport the FFB from field to the mill. Furthermore and due to the fact that FFB transportation has a strong influence on the harvesting and oil extraction, the logistic operation may weigh around the 42% of the cost of one ton of oil. In this paper is presented a literature review on models of supply chain applied to the oil palm agro industry, as well as an approach of a Mixed Integer Problem (MIP) to the optimization of one stage of the chain, the transportation of FFB.

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Programming Tools to Optimize the Transportation of Oil Palm Fresh Fruit Bunches

2 Optimization tools for the oil palm supply chain – A review At the oil palm agroindustry there have been few alternatives described for improving transport logistic ststem from the field to the mill. Jerez and Amezquita (2004) described the implementation of the FFB transportation system at Unipalma, an oil palm plantation located at the municipality of Cumaral, Meta (East region of Colombia). The system consisted of containers with capacity of 10 tons, lorries with hydraulic winch and lift with autoloader, and radios. The results of this study showed that the implemented system represents a good alternative to reduce costs per tonne, decreasing the number of vehicles used in this work and increasing storage capacity by more than 100% because of the easy use of containers in the field as a warehouse. They also suggest a strong preventive maintenance program for machinery. Mosquera and Valenzuela (2006) using time and motion, and economic feasibility techniques, carried out a study on an oil palm company located at the municipality of Zona Bananera, Magdalena. That company is considered a benchmark for the transport of RFF in Colombia. This study assessed the possibility of reducing the cost of transportation of FFB up to 42%, $7.400/FFBton (COP) to $4.600/FFBton (COP). The amendment was raised by the directly harvester´s FFB hand loading in containers, and because of the abolishing of the use of a tractortrailer which gathered the FFB on the plot´s paths and bring them to the containers, once more by hand. Ademosun (1982) proposed a model location for the production of palm oil in Nigeria, in which he determined the number, capacity and location of processing plants and routing products, so that the cost is minimized. Turner and Gillbanks (1982) argue that the type of system to be implemented in the oil palm transportation, depends on several factors such as distance traveled, the road surface, the volume of FFB to be transported, the type of soil and the reception facilities at the mill. Garcia, et al. (2007) developed a mathematical model (nonlinear mixed integer) to optimize the links of harvesting and extraction of oil palm supply chain. The authors reported that the proposed model may minimize the fixed costs of logistic infrastructure, inventory of raw materials and harvesting, lifting, transportion of the FFB, as well as on the extraction of products. Tinsay (2007) spoke about the importance to orient the competitiveness of the oil palm toward the reducing of costs through the optimization of the supply chain of palm oil, by the use of linear programming models to determine the most appropriate location for milling facilities, as well as to find optimal routes for FFB transportation. Yandra, et al. (2007) carried out an integrated decision support system based on multi-objective genetic algorithms and fuzzy logic, to optimize the supply chain of the biodiesel industry in Indonesia. The model developed is applicable for palm oil to coconut palm, and involves different providers of fruit, processing facilities and consumers. The objectives of the model aimed to minimize the total cost of the supply chain and minimize the expected number of damaged product, while the 181


optimized variables were the amount of oil sent to suppliers of biodiesel plants, the amount of biodiesel sent from plants to areas of consumption, and stocks in plants. Ibrahim (2008), in his doctoral thesis, presented the development of mathematical models of integer programming to solve a transportation problem of crude palm oil and palm kernel oil at the northern region of Peninsular Malaysia. The objective function was made to minimize distances, but also allowed to solve two transportation problems for the optimal assignation from the mills to the refineries. Gutiérrez et al. (2008) proposed a mathematical model of mixed integer linear programming, strategic planning for the biodiesel sector in Colombia. The results of the model on production, distribution of intermediate and final products and the implementation of biodiesel production plants, obtained with the support of GAMS - CPLEX, allowed to analyze the efficiency of the current chain, and to setting the logistics positions of the biodiesel plants of production, cosidered for that time. Sauian (2008) presented an study carried out at an oil palm plantation of 450 hectares, in which the performance of labor increased by 6,4% over the traditional method, by the use of a Staff assingment model for harvesting activities, based on individual skills of each worker.

3 Initiatives in other sectors. There are some examples of several sectors like forestry, sugar cane, coffee and grapes, among others. Iannoni and Morabito (2004) applied discrete simulation techniques to study the process of unloading in a sugar cane mill. By the using those techniques the performance of process was analyzed, with the aim to avoid delays for lorries and reduce the queuing at the mill. Kiranoudis Prindezis and (2005) presented a logistics management system supported on the web, to coordinate and disseminate tasks and to provide information for solving the problem of heterogeneous vehicle routing using metaheuristic techniques for use in water distribution companies. Zanoni and Zavanella (2007) proposed the use of mixed integer linear programming to the problem of sending a set of products from a single origin to a common destination. Similarly, recommend modification of known heuristics to solve it. Computational results show how the modified heuristics are effective and efficient. Ceballos, et al. (2008), described a proposal to modify the programming of commercial software used for the allocation of trucks for transporting forest products. The proposal was based on achieving harmony between two conflicting objectives: 1) minimizing the fleet of trucks and 2) reduce average working hours of drivers. To resolve this approach, they used three solution techniques belonging to multi-objective genetic algorithms: 1) Algorithm Pareto evolutionary force, 2) memetic algorithms and 3) multi-objective genetic local search, the first being best suited to the problem studied. As a result, they found that the truck fleet can be reduced by up to 13%, while working hours by 12%. 182


Kaewtrakulpong (2008) presented the results of a research conducted to improve efficiency and to reduce the cost of harvesting and transport of sugarcane in an area of 618 hectares in northeast Thailand. This was basically concentrated in two stages: 1) Data collection (surveys, interviews, time and motion studies to harvesting and transport) and 2) Carrying out two models, a crop simulation to determine the best way to introduce mechanical harvesting, using as input the size of the lots, the length of the lines, the amount of cane, and the distance to the factory, and a model of multi-objective optimization (Minimize the number of days of operation; Minimize the total travel distance of trucks and minimize the time deterioration of the cane harvested) for the transport of cane plants. According to this work, with the mechanization of the harvesting there are significant reductions in terms of cost per hectare, particularly when harvesting green cane. On the other hand, by the using of the allocation of resources obtained by the multi-objective model, the reductions in the total cost are from 4% to 9%. Bohle, et al. (2008) carried out robust optimization models to measure their effect on the uncertainty of the productivity of labor in the harvest of grapes for the wine industry. Feasible solutions of the model were studied using Monte Carlo simulations. The formulation of the model considered the grape harvest both manual and machine-and calculated how many hours of labor were required in each case. Villegas, et al. (2006) modeled the supply chain of coffee in Colombia, following a bi-objective approach, the aim was to diminish the cost without affecting the coverage of the collection centers attended by growers. Hence, they designed and implemented three algorithms: 1) Genetic algorithm non-dominated sorting (NSGA-II), 2) Pareto archive evolution strategy (PAES) and 3) Mathematical Programming. The result of this study, showed how the two first algorithms approached to the Pareto optimal front, being the first the one that best approximates the border, instead the third run in less time. Zegordi and Beheshti (2009), presented a study that integrated production programming on two-stages of a supply chain. The objective function was to minimize the delay and the total deviation of the workload assigned to the providers of their quotas. Initially, they used a whole mixed programming model and then propose the use of a genetic algorithm with three populations (MSGA), which showed better results. In accordance with the review, a model of Mixed Integer Programming is proposed to optimize the FFB transportation at one oil palm. During the next section the model is going to be presented.

4 Methodology and the model The oil palm FFB transportation process has different stages (Figure 1): it start at the plots when the FFB harvested are deposited on the internal stockpiling center; there a vehicle pick up the FFB and bring them to the external stockpiling center 183


with a cappacity of 12 ton, thereafter, another vehicle transport, from the external stockpiling center to the mill.

Fig. 1: Oil Palm FFB Transportation Process (the authors)

Given the restrictions of the software (DEMO), for this exercise there were consider only six plots (internal stockpiling centers), two internal transportation vehicles, three external stockpiling centers, and three lorries for FFB transportation to the mill. The matrix of plot productions and Transport cost, were built as follows (Tables 1 to 6). The FFB production to gather at each plot (internal stockpiling center), for the planning horizon. Plot (Internal Stockpiling Center i)

FFB Production (ton)

1

7

2

3

3

10

4

2

5

2

6

7

Tab. 1: Plot Production, for the harvesting cycle of study.

After the identification of Internal and External stockpiling centers, the cost of transport between them was estimated (Table 4). This was calculated in accordance with the distances and the cost per kilometer (Table 2); The last one was found using the fuel consumption, quality of paths and the spenditure on rent of vehicles. The next two tables shows the matrix with the cost per kilometer and the distances among stockpiling centers:

184

Programming Tools to Optimize the Transportation of Oil Palm Fresh Fruit Bunches Internal Stockpiling Center i

External Stockpiling Center j 1

2

3

1

1.317

3.244

1.790

2

1.790

3.244

1.317

3

1.317

3.244

1.317

4

1.317

1.790

3.244

5

1.317

1.317

1.790

6

1.317

1.317

1.317

Tab. 2: Cost per kilometer in accordance with the trip (COP$/km) Internal Stockpiling Center i


2

3

1

16

20

14

2

5

19

10

3

14

8

3

4

5

11

10

5

4

10

6

6

14

15

3

Tab. 3: Distances between Internal and External Stockpiling Centers (km) Internal Stockpiling Center i


2

3

1

21.072

64.880

25.060

2

8.950

61.636

13.170

3

18.438

25.952

3.951

4

6.585

19.690

32.440

5

5.268

13.170

10.740

6

18.438

19.755

3.951

Tab. 4: Internal transport cost between Internal and External Stockpiling Centers (COP$)

As well, the average speeds among Internal and External Stockpiling centers is shown as follows. Internal Stockpiling Center i


2

3

1

30

20

25

2

25

20

30

3

30

20

30

4

30

25

20

5

30

30

25

6

30

30

30

Tab. 5: Average speeds between Internal and External Stockpiling centers.

185


For the interaction between External Stockpiling Center and the mill, the cost of transportation per kilometer was COP$1.317. Furthermore in accordance with the distances the exteranl transportation cost was estimated. External Stockpiling Center j

Distance (km)

Transportation Cost (COP$)

1

8

10.533

2

12

15.800

3

8

10.533

Tab. 6: Transportation cost between External Stock Piling Centers and the mill.

Based on the parameters presented above, a model for minimizing the logistic cost by the reassingment of routes and Stockpiling centers to the availables lorries. The general model of supply chain was consider, but limited to the link of FFB transportation. The model of Mixed Integer Programing built was programmed into the DEMO version of GAMS V23.0. The Planning Horizon for this excercise was one day. Despite the model may be used with an extra number of stockpiling centers, the amount of plots, external stocpiling center and vehicles were reduce to fit on the restriction of use on the DEMO version. In instance, there were only considered six plots, three external stockpiling centers, two vehicles for internal transportation and thre lorries for FFB transportation to the mill.

5 Mixed Integer Problem Sets: Set of internal stoockpiling centers (plots) (i). i=1,2,.., m. (m=6) Set of external stockpiling centers (j). j=1,2,…,n. (n=3) Set of internal transportation vehicles (k). k=1,2,...,r. (r=2) Set of external transportation vehicles (l). l=1,2,…, s). (s=3)

6 Parameters: Mj= Capacity of the external stockpiling centers j to store the FFB that come form internal stockpiling centers i. (ton). DIij= Distance from the internal stockpiling center i to the external stockpiling center j (km). DEj= Distance from the external stockpiling center j to the mill (km). Cijk= Trip cost of the vehicle k between internal stockpiling center i and the external stockpiling center j (COP$/trip). Sjl= Trip cost of the vehicle l between the external stockpiling center j and the mill (COP$/trip). TCk= Time of loading and unloading of FFB at the vehicle k. (hours). 186


TCPl= Time of loading of FFB at the vehicle l. (hours). TD= Time of unloading of FFB at the mill. (hours). VIijk= Speed on the trip of vehicle k from the internal stockpiling center i to the external stockpiling center j (km/h). VEjl= Speed on the trip of the vehicle l from the external stockpiling center j to the mill (km/h). CAP= Capacity of Mill processing (tonne/day). CAPk= Capacity of vehicle k (tonne/trip). CAPl= Capacity of vehicle l (tonne/trip). TMK= Maximum day time of work for internal transportation vehicles (hours) TML= Maximum day time of work for external transportation vehicles (hours) PROi= Production of plot (internal stockpiling center) i.

7 Variables: Xijk= FFB to be transported from the internal stockpiling center i to the external stockpiling center j, with the vehicle k. (ton). Yjl= FFB to be transported from the external stockpiling center j to the mill, with the vehicle l. (ton). Qijk= Binary variable (Qjik=1, if the FFB are transported from the internal stockpiling center i to the external stockpiling center j with the vehicle k; Qjik =0, in other case) Pjl= Binary variable (Pjl=1, if the FFB are transported from the external stockpiling center j to the mill; Pjl=1, in other case) Z= Objective Function, minimize the whole cost of transportation (COP$/FFBton)

8 Objective Function: Minimize the cost of transportation: m

MinZ 

n

r

n

s

   Cijk Qijk    S jl Pjl i 1 j 1 k 1

j 1 l 1

m

 PRO

i

i

9 Constraints: The production of a plot (internal stockpiling center) must be transported to a sinngle stockpiling center by the same internal transportation vehicle. X ijk  Qijk * CAPk k

i, j , k

The whole production of a plot (internal stockpiling center) must be transported to a single external stockpiling center. n

r

j

k

 X

ijk

 PROi

i

187


The whole FFB stored at each external stockpiling center must be transported to the mill. m

r

s

i

k

l

 X ijk   Y jl j Balance equation:the whole FFB sent from all the stockpiling center must be deliver from the external stockpiling center. n

s

m

j

l

i

 Y jl   PROi Constraint of the processing capacity of the mill. .

n

s

j

l

 Y

jl

 CAP

Constraint of the assignment of the same vehicle to an internal stockpiling center. m

r

i

k

 Q

ijk

 1 j

Constraint of the FFB transportation in the same vehicle from the externalstockpiling center to the mill. s

P

jl

 1 j

l

Y jl  CAPll * Pjl j , l

Constraint of external stockpiling center capacity. m

r

 X i 1 k 1

ijk

 M j j

Maximum time of work vehicle l. n

 DE jl

j 1



  VE

jl

  TCPl  TD Pjl  TM ; l  

Maximum time of work vehicle k. m

n

 DI ij

  VI

 ijk X ijl  0, Y jkl i 1

j

  TC k Qijk  TM ; k   0

10 Results The model executes in 0,031 seconds in a laptop with a 1,66GHZ Intel Centrino Dual Core Processor, of 2MB of RAM.

188


Fig. 2: Assignment with the model approach to the internal vehicle 1.

The model showed the assignment of all internal stockpiling center to one internal vehicle. At the same time, the whole production of each plot was transferred to a single external stockpiling center. The amounts transported to external stockpiling centers were 12, 9, and 10 ton, respectively (Figure 2). Those external stockpiling centers were served by a single vehicle, which transported the FFB to the mill.

Fig. 3: Assignment with before the model approach, to the vehicle 1.

189


Based on the model proposed, the cost of transportation was COP$24.694 per FFB ton. In order to determine the effect of the proposed model on the base case cost, it was required to compare the results with the initial assignation (Figure 3). In the base case, using a single vehicle, the amounts transported to the external stockpiling centers 1, 2, and 3 were 12, 12 and 7 FFB ton, respectively. Then, another single vehicle upload the FFB at the external stockpiling center to the mill. This arrangement causes a transportation cost of COP$41.301. In accordance with that, the transportation cost may be reduced up to 40%, by the using of the model

11 Conclusions In this approach a Mixed Integer Programming (MIP) model was proposed. This allowed assigning the production and routes to the stockpiling centers and vehicles available. The model proposed offered a reduction of 40% on the transport cost compared with the base case. The programming models are an alternative that can be used at the supply chain or oil palm.

References Fedepalma (2009). Anuario estadístico de Fedepalma. Colombia Ademosun, O. C. (1982). Location-allocation models for oil palm production in Nigeria based on the feasible set approach. International Journal of production Research. Vol. 20, No. 2, 211– 226p. Bohle, C/Maturana, S/Vera, J. (2008). A robust optimization approach to wine grape harvesting scheduling. European Journal of Operational Research. Ceballos, L/Marinado, D/Matamala, M. (2008). Transporte de productos forestales bajo un enfoque multiobjetivo. XIV Latin Ibero-American Congress on Operation Research (CLAIO). Book of Extended Abstracts. Corley, R H V/Law, I H. (2001). Ripening, harvesting and oil extraction. The planter, vol 77. 507524 p. Duarte y Guterman. (2009). Informe de actualización de costos de producción del aceite de palma. Bogotá, Colombia: Fedepalma. Fontanilla, C/Pachón, S/Castiblanco, J/Mosquera, M/Sanchez, A. (2010). Referenciación competitiva a los sistemas de evacuación y alce de fruto. Bogotá, Colombia. Ed: Area 51 Publicidad y Comunicación, 48p. Fontanilla, C./Castiblanco, J. (2009). Cable vía en la cosecha de la palma de aceite. Bogotá, Colombia. Revista Palmas Vol3, No4, 53-64p. García, R/Martínez, M/Palacios, F. (2007). Tactical and operative optimization of the supply chain in the oil palm industry. Universidad de los Andes. Colombia. Tesis Doctoral. Gutierrez. (2008). Planificación estratégica del biodiesel en Colombia. Book of Extended Abstracts. XIV Latin Ibero-American Congress on Operation Research (CLAIO). Iannoni, M/Morabito, R. (2006). A discrete simulation analysis of a logistics supply system. Transportation Research Part E. 191-210 p. Ibrahim, S. (2008). Transportation optimization model of palm oil products for northern peninsular Malaysia. Doctoral dissertation. Universiti Sains Malaysia.

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Programming Tools to Optimize the Transportation of Oil Palm Fresh Fruit Bunches Jerez, J/Amézquita, M. (2004). Transporte de fruta en cajas en Unipalma S.A. Revista Palmas. Vol. 25, No. Especial 2, 472-175 p. Kaewtrakulpong, K. (2008). Multi-objective optimization for cost reduction of mechanical sugarcane harvesting and transportation in Thailand. Dissertation for the degree in Doctor of Philosophy in Agricultural Science, submitted to the Graduate School of Life and Environmental Sciences, University of Tsukuba. LMC International Ltd. (2008). Oilseeds and oilseed products. Outlook for profitability to 2020. Mosquera, M/Valenzuela, J. (2006). Estudio de logística para el proceso de transporte de fruto de aceite en Colombia. Revista Palmas. Vol. 27, No. 4, 55-64 p. Prindezis, N/Kiranoudis, C. (2005). An internet-basedlogistics management system for Enterprise chains. Journal of food engineering.Vol. 70, 373-381 p. Sauian. (2008) OR in Agriculture: The Use of Assignment Model. Proceedings of the Third Meeting of the EURO Working Group on Operational Research (OR) in Agriculture and Forest Management (EWG-ORAFM). Tinsay, E. (2007). Introducción a la red logística en el aceite de palma. Revista Palmas. Vol. 28, No. Especial, 321-327p. Turner, P/Gillbanks, R. (1982). Oil palm cultivation and management. The incorporated society of planters. Kuala Lumpur. Villegas, J G/Palacios, F./Medaglia, A. (2006). Solution methods for the bi-objective (costcoverage) unconstrained facility location problema with an illustrative example. Ann Oper Res, 108-141p. Yandra/Marimin/Jamaran, I/ Eriyatno/Tamura, H. (2007). An integration of multi-objective genetic algorithm and fuzzy logic for optimization of agroindustrial supply chain design. Proceedings of the 51st Annual meeting of the ISSS. Tokyo, Agosto 5-10. Zanoni, S/Zavanella, L. (2007). Single-vendor single buyer with integrated transport-inventory system: Models and heuristics in the case of perishable goods. Computers and industrial engineering. Vol 52, 107-123 p. Zegordi, S/Beheshti, M. (2009). A multi population genetic algorithm for transportation scheduling. Transportation Research, Part E, 946-949 p.

191

Modelling Freight Flow Information within the Maritime Transport Chain: Benefits and Effects of „Estimated Time of Arrival“ (ETA) Messages

Ralf Elbert, Arzum Oezgen, Fabian Walter

Abstract International maritime logistics as a crucial link in total supply chain still maintains its importance regarding to increased demand in manufacturing and services industries for international transport and logistics activities. From macro perspective this increased demand is initiator for global labor division and containerization of value added products. From micro perspective costs and capital lockup could be a high pressure for individual actors within the transport chain. Both these issues result in a need for high automatisation level and larger need for efficient management of logistics processes. The maritime transport chain has a heterogeneous structure in nature. The various actors could be named as agents who their inevitable functional role in the logistics chain must be coordinated without interfere with their target self-interest and business concepts. This structure has effected high distribution of tasks and thus needs seamless flow of information leading to a very high demand on inter-organisational coordination between the actors. Producing industry already implemented planning and simulation concepts such as Manufacturing and Enterprise Resource Planning (MRP I/II and ERP) and Supply Chain Management (SCM). One of the important information that is missing along maritime transport chain is “estimated time of arrival” (ETA) of containers. Sufficient and well structured freight flow information makes daily operations such as transport, transfer, handling and storage services which performed by logistics agents become more efficient. Established communication behaviours within the maritime transport chain are preventing a transparent information flow. Besides agents which have roles in the beginning of the transport chain do not benefit directly from providing valuable information such as ETA and prevent open innovation processes. The objective of this paper is describing the effects and benefits of ETA messages within the maritime transport chain with development of a comprehensive logistics model using system dynamics. ETA aims and requirements will be analysed. Modelling ETA effects will show, whether benefits of seamless freight flow information at the earliest point of availability are possibly conflicting or even cancelling each other. A general structure of maritime logistics processes and issues of port hinterlands 193


and providing ETA is represented. Afterward a review of problems related information flow especially ETA of containers in maritime logistics activities is covered. For this aim a case study is constituted on the basis of Hamburg Harbour Logistics Cooperation (HHLA), Hapag-Lloyd and Deutsche Bahn. The positive effect of ETA of containers on maritime transport chain is demonstrated. The expected results are providing an understanding for giving valuable ETA messages, to increase efficiency along the maritime transport chain and stabilizing actors’ planning, by identifying fluctuation changes in freight flow at the earliest point. Furthermore profitability of ETA adoption along the maritime transport chain will be shown.

Keywords: Maritime transport chain, Efficient freight flow information, Estimated time of arrival message

1 Introduction International maritime logistics as a crucial link in total supply chains still maintains its importance regarding to increased demand in manufacturing and services industries for international transport and logistics activities. From macro perspective this increased demand is initiator for global labor division and containerization of value added products (Notteboom 2004). From micro perspective costs and capital lockup could be a high pressure for individual actors within the transport chain. Both these issues result in a need for high industrialization level and larger need for efficient management of logistics processes – also for the maritime transport chain. The maritime transport chain has a heterogeneous structure in nature. The various actors could be named as agents who their inevitable functional role in the logistics chain must be coordinated without interfere with their target self-interest and business concepts (Roorda et al, 2010). This structure has effected high distribution of tasks and thus needs seamless flow of information leading to a very high demand of inter-organisational coordination between the actors. Production industry already implemented planning and information concepts such as Manufacturing and Enterprise Resource Planning (MRP I/II and ERP) and Supply Chain Management (SCM) (Rönkkö et al, 2007). In trade Efficient Consumer-Response (ECR) and Collaborative Planning, Forecasting and Replenishment (CPFR) was implemented for information at the point of sale in real time (Corsten/Gabriel, 2004). One of the important information for the industrialization along maritime transport chain is „estimated time of arrival“ (ETA) of containers. Sufficient and well structured freight flow information makes daily operations such as transport, transfer, handling and storage services which performed by logistics agents become more efficient, but established communication behavioral routines within the maritime transport chain are preventing a continuous information 194

Modelling Freight Flow Information within the Maritime Transport Chain

flow without time delays in real-time (Schuh, 2006). Besides agents which have roles in the beginning of the transport chain do not benefit directly from providing valuable information such as ETA and prevent open innovation processes (Reichwald/Piller, 2006). The resulting information run-time combined with the capacity restrictions of the various actors and transhipment processes as well as a decentralized planning approach are leading to the maritime reflection of the bullwhip-effect, known from industrial demand fluctuations in supply chains (Syska, 2006). This so called Forrester-effect, describing the phenomenon of self amplifying fluctuations, is especially basing on uneven capacity utilization and high stocks (Lödding, 2008; Forrester, 1972). The objective of this paper is to describe the effects and benefits of ETA messages for the industrialization of the maritime transport chain. Therefore a comprehensive logistics model using system dynamics will be developed. Modelling ETA effects will show, whether benefits of a specific type or form of accurate seamless freight flow information at the earliest point of availability are possibly conflicting or even cancelling each other.

2 The maritime transport network Since traces of the economic turmoil could be seen over the global economy, questions and discussions around how to be prepared for future is going on. Since maritime industry is the main part and carrying system of the world’s 90% of trade volume, it would be a well matched time to focus on the appropriate strategies to enhance maritime logistics process and activities (Brooks et al, 1992; Maritime International Secretariat Services Ltd, 2006). Since its appearance on the international scene in the 1960s, containerization has accompanied the expansion of the world economy in a virtuous circle. Hayuth (1992) has indicated that two factors largely explain the success of containerization. The first is containerization increased the productivity regarding cargo handling in ports which accounted for the rapid success and diffusion of containerization. The second and more gradual process involved the refinement of the container networks of the major shipping lines. The initial route for the major carriers was on the East-West routes which linked the three poles of the global economy (Rimmer, 2004) but, with the growing liberalization of maritime transport in the 1980s, they began to serve the North-South markets as well (Hoffmann, 1998; Fremont, 2007; Imai et al, 2006; Slack, 1985). Besides the growth of networks and services, cooperation between the maritime transport agents such as, deep sea carriers, ocean freight forwarders, terminals (ports and hinterland), freight operators, short-sea shipping companies and container depots as well as rail, road and barge carriers (see figure 1) became more important including ports as central link in transport chains (Heaver, 2002). Enlarging and concentrating the flows between the ports necessitates acquiring a balanced 195


and fluent flow of containers between these agents. Delivery service constitutes more and more a knock-out criterion, as maritime transport became a inherent part of complex logistics concepts based on the division of labor. Thus, it is necessary to build new maritime transport concepts and cooperations in order to increase service satisfaction, e.g. real-time information, accurate time windows and goods tracking systems (Tseng/Yue, 2005; Thomas/Griffin, 1996).

Fig. 1: Actors within the maritime transport chain

3 Industrialization strategies for maritime transport chain 3.1 General requirements maritime transport chains In supply chain management literature there are several redesign modeling strategies which an extensive review conducted by van der Vorst and Beulens (2002). They identified a generic list for these strategies to facilitate the redesign process and attain joint supply chain objectives (van der Vorst et al, 2005): –

–

– –

Reduce lead times (e.g., implement information and communication technology (ICT) systems for information exchange and decision support, increase manufacturing flexibility or reallocate facilities). Create information transparency (e.g., establish an information exchange infrastructure in the supply chain and exchange information on demand/ supply/ inventory or work-in-process, standardize product coding). Synchronize logistical processes with consumer demand (e.g., increase execution frequencies of production and delivery processes, decrease lot sizes). Coordinate and simplify logistical decisions in the supply chain (e.g., coordinate lot sizes, eliminate human interventions and introduce product standardization and modularization).

As stated a typical logistics networks necessitates multiple parties, who have several and possibly conflicting objectives. Operations and activities of one actor in the network will influence the process and activities feature and characteristics of next 196


actor. This issue involves the alignment of partner strategies and interests, high intensity of information sharing, collaborative planning decisions and shared IT tools. Usually these requirements restrain the full integration between actors in logistics network. Even if there is a strong cooperation and partnership among logistics nodes, practically there are several contradictions such as local versus global interests and insufficient information sharing on planning and scheduling activities such as for example, inventory and capacity levels (Terzi/Cavalieri, 2004).

3.2 Research contribution: ETA in the maritime transport chain Maritime transport chains involve the logistics activities that are performed by the seaport and its suppliers and sub-contractors to complete the transport activities. Each company performs a set of activities that are interrelated and complementary. The execution of these activities involves exchange of information either between the working groups of the seaport or among seaport and the suppliers and subcontractors (Makris et al, 2008; Coronado Mondoragon et al, 2009; Garcia-Flores et al, 2009). Besides agents which have roles in the beginning of the transport chain do not benefit directly from providing valuable information such as „estimated time of arrival“ (ETA) and prevent open innovation processes. ETA already can be provided within a company structure or between independent partners. But concerning actors in a competitive relationship ETA could not been realized. The high division of labor in maritime transport chain leads to such a competitive relationship by containing different actors and business models. The business process for the maritime logistics involves a large number of interrelated partners. The main participants are as follows: Logistics agents such as deep sea carriers, ocean freight forwarders, terminals (ports and hinterland), freight operators, short-sea shipping companies and container depots as well as rail, road and barge carriers could be named as agents who their inevitable functional role in the logistics chain must be coordinated without interfere with their target selfinterest. The business process is complex for a number of reasons (Makris et al, 2008): –

– – –

The containers are continually in a movement and related data regarding their position and place have to be transferred to the next actors in sequence in a fast, easy, and reliable way. The repair work is not known from the beginning and a lot of repair items are identified during inspection at the shipyard. A large number of actors, performing transport activities, are involved in the data transfer. The activities performed in the maritime logistics network by agents are interrelated. 197


Due to the nature of the maritime logistics networks the partners must communicate in a fast, easy, and reliable way by exchanging information about the container, the casualties that may have occurred as well as information for coordinating purposes. The main part of the business process takes place around the communication of the agents with the seaport that cooperates to specify the position and place of container and estimated time arrival of it. The business process can grow up in a very high degree if we consider the involvement of the multiple agents and the related companies that participate in the maritime logistics transport (Odendahl et al, 2000; Pedoroso/Nakano, 2009). Logistics networks involves interdependency between logistics agents and this necessitates trust and information flow between each agents processes which this constitution defined in literature as that companies will lose bargaining power and therefore the ability to control profits as suppliers or customers gain knowledge (Barratt/Oliveira, 2001). This leads us to the following requirements on model design (van der Vorst et al, 2005): – –

– –

Model elements and relationships: Explicit notion of actors, roles, control policies, processes, and flows in the model. Model dynamics: Determine the dynamic system state, calculate the values of multiple performance indicators at all times, and allocate performance indicators to the relevant supply chain stages. User interface: Domain related contribution of the problem owner in terms of alternative solutions. Ease of modeling scenarios: Reusable models may help to increase the speed of modeling and analyzing alternative scenarios.

As mentioned before the objective of this paper is describing the effects and benefits of ETA messages within the maritime transport chain with development of a comprehensive logistics model using system dynamics. Modelling ETA effects will show whether benefits of seamless freight flow information at the earliest point of availability are possibly conflicting or even cancelling each other.

4 Modeling freight flow information within the maritime transport chain – Case study based on analysis of ETA 4.1 Review of simulation tools and requirements for model description of the maritime transport chain By modelling ETA the complexity of real maritime environment can be reduced for the key parts concentrating on the nodes and edges of the transport network. The paper’s case deals with modelling Ship-ETA on the import side regarding to a continuous flow over time. We have considered ETA problem within maritime 198


transport as a stock and flow problem and we used system dynamic approach. Feedback loops and time delays that affect the behavior of the entire system help to understand behavior within the complex system over time (Forrester, 1999). In the past, many modeling and simulation tools for supply chain and logistics networks have been developed. The modeling characteristics of these packages are given in short. DYNAMO was the first system dynamics simulation language. It provides an equation based development environment for system dynamics models. IThink/Stella Originally introduced on the Macintosh in 1984, the Stella software provided a graphically oriented front end for the development of system dynamics models. The stock and flow diagrams, used in the system dynamics literature are directly supported with a series of tools supporting model development. IThink, PowerSim and Powersim were later developed for the development of system dynamics models that also facilitates packaging as interactive games or learning environments. Vensim developed in the mid 1980s which is an integrated environment for the development and analysis of system dynamics models. Exposé is a Microsoft Excel add-in that supports the creation of causal loop/stock and flow diagrams in parallel with spreadsheet development. We have used AnyLogic. AnyLogic supports a variety of approaches to discrete event and continuous modeling, such as process flow diagrams, system dynamics, agent-based modeling, state charts and equation systems. Some of the studies conducted for logistics network analysis could be summarized as follow. Minegishi and Daniel (2000), has used to show how system dynamics could contribute to improving the knowledge of the complex logistics behavior of an integrated food industry (van der Vorst et al, 2005). Lai et al (2003) has developed an alternative view of JIT by using system dynamics (SD) that concentrates on analyzing the logistics policies of a company and understand the customers, competitors, and suppliers interactions that shape the company’s performance over time. In this model, the strategies and action steps were addressed and adopted and the resulted in improvement in inventory control, quality and productivity (Lai et al, 2003).

4.2 Case – Hamburg maritime transport chain As a initial situation the long-term projected container handling volumes in the German seaports required improvements in resource management along the entire transport chain. Necessary participating actors such as deep sea carriers, terminals, rail operators and railway companies were needed. After interviewing representing actors they were brought together in round-table discussions and workshops focussing on the positive effects of ETA of containers on maritime transport chain. In current situation, coordination of maritime logistics actors is a challenging task. One of the main challenges for all actors in the whole chain is the lack of bior multilateral coordination and the accompanied numerous inaccuracies. This 199


brings the following challenging issues which are contrary to the efficient handling of increasing flows of goods into the hinterland by rail: – – – –

No continuous information availability, transparency and speed of the transport chain. Low standardization of IT interfaces and data reported by the actors of the intermodal transport chain. High transfer rate for shipping container on loading. Notification of inflow data from ships, containers and trains.

Regarding to the lack of information (time schedules, transfer dates, etc.) about the containers there is an unnecessarily effort performed by the quay operators. Failure in fulfilling accurate, enough and on time information, causes unnecessary handling costs for the storage and retrieval of containers in the terminal which should deal with a high rate of load-unload activities for imported containers. The same problem exists in the export terminals of maritime logistics hinterland. Lack of sufficient information for an effective scheduling and resource planning, increases the train processing time. Furthermore, lack of conveying information regarding schedule changes reported by ships causes many disorders or significant additional expense in the disposition of container trains on the import and the temporary assignment of reserves (intermodal wagons and locomotives). On the other hand, delays without transferring information in some cases cause cancellation of export trains, charging containers and impede the efficient stowage planning on ships. In view of the presented challenging areas and the projected container volume for the future years, it is essential to use the scarce existing capacity of the actors more efficient to handle the expected transport volume growth. For this reason, the project focuses on the benefit and advantages using information and communication systems between transport network actors and it has determined to monitor the following goals: – – –

Shortening the train process times by increasing the process reliability in the port. Efficiency increases along the transport chain port/rail-transport by inland logistics process and data flow optimization. Performance enhancement through the building of capacity to prevent earlier data exchange and processing of internal information.

To increase performance in the transport chain the reliability of operational planning a standardized and reliable data exchange at an early point will be constituted. The ability of actors for creating, providing and using advanced notifications regarding anticipated container arrivals is analysed by considering ETA. For full 200


consideration of the effects of ETA-messages both the import and export side have to be considered. This will effect development of business processes such as import and export container streams. In this paper we are concentrating on import. On the import side a more reliable and faster advancing notification of the ship's ETA by the deep sea carrier to the quay operators (terminal) is planned (see figure 2). Furthermore, a provision of the unloading intervals for import containers is provided by the quay operators. In addition, participation in the adjustment of standards for a port-IT platform is intended.

Fig. 2: Projectscope: Import direction

On the export side, the introduction of constant, timely and reliable reporting on the expected time of arrival of the train (ETA-rail) in the port (the port railway infrastructure) by the railway company to the quay operators, the shipping company and the port railway are planned (see figure 3).

Fig. 3: Projectscope: Export direction

The provision of these messages has to end up in a check, using iterative loops between the railway company, the port railway and quay operators, to determine whether the container on the export train will reach the vessel in time or not. In addition, based on the cooperation of actors (partners) within the implementation and 201


evaluation of activities and processes in supply chain detecting exceptions and enabling quick responses would be possible. The early recognition of critical states gives opportunity to plan additional actions. This also will help to classify train or ship delays as critical within the logistics process. This control will improve capacity utilization.

4.3 Proposed Model for demonstration of effects of ETA on import direction In the system dynamics model carriers arrive with different randomized container loads which have to be unloaded. Variations in arrival time and thus a key factor for ETA-messages is modelled by scalable variables, triggering the event by using a triangular distribution, which is a continuous distribution bounded on both sides, using a minimum (min), a maximum (max) and most likely (mode) representing the exact ETA. 2

min

2

x

0

Factors such as; Integrating capacity restriction as causal loops, handling problems, congestions or rescheduling of unloading are included in the model. After the container vessel arrives in the port it will be unloaded over time and containers or entities are flowing to the next stock in model, the terminal. From here the containers will be transhipped to rail, depending on both the capacities of terminal and rail operations. The flow to the hinterland or on-carriage by rail is still effected by upstream given information and ends into the hinterland stock which closes the model view. Implementing ETA or more precise increasing the quality of ETA-messages will decrease the number of rescheduling activities of ship arrivals. The model also includes ETA-messages triggered by the deep sea carrier, which are delivered to the terminal and the rail actor (see figure 4).

202


Fig. 4: Model for demonstration of effects of ETA on import direction

5 Discussion of the first results and further research Receiving ETA message in the earliest point is increasing the efficiency of the quality factors. For instance lower container handling activities has a positive effect on the limited capacities of handling and transhipment. The causal loops and limited capacities in storing are also affected by this growth. The provision of ETA over the whole transport chain prevents an excessive growth in one stock. The model shows that the flow to the next stock increases, too. Thus more containers will be transhipped to the hinterland over time. Providing ETA at the earliest time available to all involved downstream actors enables better planning and faster transhipment along the transport chain. Less costs in transhipment and storing are reached by decreasing rescheduling depending on short-term order and planning changes. This faster handling and transhipment from container of the vessel into the hinterland promises better turnovers for the actors involved. Depending on the position in the maritime transport chain and on the cost and income functions, faster transhipment rates and efficient handling of containers may generate more revenue than storing. Taking a look on both sides of freight flow for export and import the following benefits for the actors such as deep sea carrier, terminal and rail operator were identified. 203


For deep sea carriers ETA, provided by export trains, enables loading of empty instead of the cancelled containers, if the train is too late for dispatching. Thus efficiency of stowage increases. In terminals ETA, provided by export trains combined with a mirror of loaded containers gives enough lead time information about the wagons and containers on train for efficient resource planning and less train handling time. ETA either provided on import or export side enables the terminal to increase the efficiency in handling and storage of containers, too. For rail operators, ETA provided by carriers, decreases disorders and additional overhead in container disposition on import trains, as well as provision of transport reserves (wagons and traction vehicles). Furthermore there is the possibility to increase the amount of trains driven over time by establishing faster clock rate transporting block trains. For all involved actors there are individual optimization structures depending on the prices. These prices do not only include the handling prices but also the prices for establishing ETA itself. So the price of ETA provision and handling directly takes effect on the industrialization of the maritime transport chain and thus the optimization of profits. Besides the identified effects and benefits of ETA, it is important to emphasize that capacity planning has to be optimized in a mutual approach. The actors have to adopt successful innovations to implement the need for industrialization of the maritime transport chain. ETA is a key for providing the needed information, but now the quality of this information has to be considered, too. Further research has to analyse which concept and quality or at least which minimum requirements ETA has to meet. The speed, or better the maximum delay of provision has to be identified. Nevertheless ETA not only means better information flow but also new costs for interfaces and information transactions. For this reason in the next interview rounds the model will be complemented by actor’s data and restrictions and the design of the characteristics will be specified.

References Barratt, M. and A. Oliveira. (2001): Exploring the experiences of collaborative planning initiatives; International Journal of Physical Distribution & Logistics Management, 31, 4, pp. 266289. Coronado Mondragon, A. E. C., Lalwani, L., Coronado Mondragon, E. S. C., Coronado Mondragon, C. E., (2009): Facilitating multimodal logistics and enabling information systems connectivity through wireless vehicular networks; International Journal of Production Economics, 122, pp. 229-240. Corsten, Daniel; Gabriel, Christoph (2004): Supply Chain Management erfolgreich umsetzen. Grundlagen, Realisierung und Fallstudien; mit 20 Tabellen. 2., verb. Aufl.; Springer; Berlin. Forrester, Jay W. (1972): Grundzüge einer Systemtheorie; Gabler Verlag; Wiesbaden. Forrester, Jay W. (1999): Industrial dynamics. 4. Dr. Waltham: Pegasus Communications.

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Modelling Freight Flow Information within the Maritime Transport Chain Garcia-Flores, R., Wang , X. Z., Goltz, G.E., (2000). Agent-based information flow for process industries' modeling, Computers and Chemical Engineering 24, pp. 1135-1141. Hayuth, Y., (1992): Multimodal freight transport.; In: Hoyle, B., Knowles, R. (Eds.), Modern Transport Geography. Belhaven, London, pp. 200–214. Hoffmann, J., (1998). Concentration in Liner Shipping: its Causes and Impacts for Port and Shipping services in Developing regions. PDF document http://www.eclac.cl/transporte/ (Economic Commission for Latin America and the Carribean). Imai, A., Nishimura, E., Papadimitriou, S., Liu, M., (2006): The economic viability of container mega-ships. Transportation Research Part E 42 (1), pp. 21–41. Lai, C.L., Lee, W.B., Ip, W.H. (2003): A study of system dynamics in just-in-time logistics; Journal of Materials Processing Technology 138, pp. 265–269. Lödding, Hermann (2008): Verfahren der Fertigungssteuerung. Grundlagen, Beschreibung, Konfiguration. 2., erw. Aufl. Berlin, Heidelberg: Springer-Verlag (VDI-Buch). Makris, S., Xanthakis, V., Mourtzis, D., Chryssolouris, G., (2008): On the information modeling for the electronic operation of supply chains: A maritime case study; Robotics and ComputerIntegrated Manufacturing, 24, pp. 140–149. Maritime International Secretariat Services Ltd (2006): International Shipping Carrier of World Trade, IMO WORLD MARITIME DAY 2006. Mary R. Brooks; Kenneth J. Button (1992): Shipping within the framework of a single European market . Transport Reviews, Volume 12, Issue 3 July 1992 , pp. 237 – 251. Notteboom, T. H. (2004): Container Shipping and Ports: An Overview; Review of Network Economics; pp. 1-27. Odendahl, C., Wieland, P., Weitzenbock, E., Jaramillo, D., Makris, S., Cacho, A., Soares, GC. M.(2000): a Virtual Enterprise Network for the Maritime Domain, Computer Applications and Information Technology in the Maritime Industries. COMPIT’2000, pp. 323–14. Pedroso, M. C., Nakano, D. (2009): Knowledge and information flows in supply chains: A study on pharmaceutical companies; International Journal of Production Economics, pp. 376-384. Reichwald, R.; Piller, F. (2006): Interaktive Wertschöpfung – Open Innovation, Individualisierung und neue Formen der Arbeitsteilung; Gabler; Wiesbaden 2006. Rimmer, P., (2004): Global Xows, local hubs, platforms and corridors; regional and economic integration in Northeast Asia; Journal of International Logistics and Trade 1 (2), pp. 1–24. Roorda, M. J.; Cavalcante, R.; McCabe, S.; Kwan, H. (2010): A conceptual framework for agentbased modeling of logistics services; Transportation Research Part E; pp. 18-31. Rönkkö, M.; Kärkkäinen, M; Holmström, J. (2007): Benefits of an item-centric enterprise-data model in logistics services: A case study; Computers in Industry; pp. 814–822. Sahin, F.,Robinson, E.P. (2002): Flow coordination and information sharing in supply chains: review, implications, and directions for future research; Decision Sciences, 33(4), pp. 505– 536. Schuh, G. (2006): Sm@rt Logistics: Intelligent networked systems; CIRP Annals – Manufacturing Technology; pp. 505-508. Slack, Brian (1985): 'Containerization, inter-port competition, and port selection', Maritime Policy & Management, 12: 4, pp. 293 – 303. Syska, Andreas (2006): Produktionsmanagement. Das A – Z wichtiger Methoden und Konzepte für die Produktion von heute. Wiesbaden: Betriebswirtschaftlicher Verlag Dr. Th. Gabler GWV Fachverlage GmbH Wiesbaden. Terzi, S.; Cavalieri, S. (2004): Simulation in the supply chain context: a survey;Computers in Industry Volume 53, Issue 1, January 2004, pp. 3-16. Thomas, D.J. and Griffin, P.M. (1996) Invited review coordinated supply chain management, European Journal of Operational Research, Vol. 94, pp. 1-15. Tseng, Y.-Y, Yue, W. L. (2005): The Role of Transportation in Logistics Chain; Proceedings of the Eastern Asia Society for Transportation Studies, 5, 1657-1672.

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Ralf Elbert, Arzum Oezgen, Fabian Walter Van der Vorst, J.G.A.J. and A.J.M. Beulens. (2002): Identifying sources of uncertainty to generate supply chain redesign strategies; International Journal of Physical Distribution and Logistics Management. 32 (6): pp. 409- 430. Van der Vorst, J.G.A.J. , Tromp, S, van der Zee, D.-J., (2005): A Simulation Environment for the Redesign of Food Supply Chain Networks: Modeling Quality Controlled Logistics; Proceedings of the 2005 Winter Simulation Conference M. E. Kuhl, N. M. Steiger, F. B. Armstrong, and J. A. Joines, eds. Wong, C. W. Y., Lai, K-H., Ngai, W. T. (2009): The role of supplier operational adaptation on the performance of IT-enabled transport logistics under environmental uncertainty; International Journal of Production Economics, 122, pp. 47–55.

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3E Logistics – Electric Transport Routing

Matthias Klumpp, Sascha Bioly, Tristan Keusgen

Abstract Transports with electric vehicles will be a dominant research question for the coming years. But whereas up to now main research focus was put on engineering questions about batteries, materials and automotive construction as well as electricity infrastructure for recharging the main questions for efficient E-Logistics will be the analysis and change of operative processes in the wake of this new propulsion system mainly in road transport. Not only loading and unloading but also routing decisions and therefore software and systems in logistics companies will have to be adapted to new restrictions due to for example smaller ranges of electricdriven road vehicles. This paper describes the dependencies of the three areas ecological logistics concepts, electricity production and electric routing as a “3E Logistics” concept to be considered if green logistics will be implemented by practical use of electric vehicles, especially for last mile transports. This allows for a future research into an integrated concept for electric road transport in logistics. Some practical questions regarding routing details with such vehicles are also discussed in a practical example with real life transport data from DB Schenker Duisburg. These outlines should help to pave the way for an efficient and at the same time ecological use of electric road vehicles in logistics in the future.

Keywords: E-Mobility, Electric Process Redesign, Electric Transport Routing

1 Introduction One of several major trends in logistics calling for innovation is the question of sustainability (cp. Halldorsson/Kotzab/Skjott-Larsen 2009, Klaus 2009, Klumpp 2009). Whether they are called green logistics, sustainable logistics or different, altogether such concepts are looking out for innovations regarding a reduced resource and energy consumption and emission reduction of pollutants as e.g. CO2, other green house gases (GHG), NOx or others related to goods transport and storage in supply chains (cp. Browne et al. 2008, Zelewski/Saur/Klumpp 2008, Al-Mansi et al. 2008). A distinguished area of innovation is the changeover from existing motor concepts (burning diesel) towards other new propulsion systems as e.g. hy207


brid drives and electricity motors in road transport as well as other transport modes (cp. Stan 2005, Klaus/Krieger 2004). This development is up to now mainly discussed and tested in personal transport (cars) but will soon also include the goods traffic by lorry (cp. Hoepke/Breuer 2008, DePauli-Schimanovich/Weibel 2004, Heinloth 2003). In order to structure this upcoming innovation strand in logistics the following figure provides a first conceptual framework calling for ‘3E Logistics’ as three subject areas have to be addressed: (A) On an ecological level integrated concepts have to be developed in order to embed ecological questions into general logistics questions as e.g. location decisions and problems, transport mode decisions and supply chain design. This area mainly calls for decision support systems and ecological criteria to be integrated in existing information and decision support systems. Regarding transport modes the question of electric mobility will be a major topic in order to implement green logistics concepts. (B) On a second level the connected question of electricity production will be of importance as a change to electric driven vehicles not automatically will result in low resource needs and emissions. Therefore green logistics concepts including electric transport will have to integrate and answer the question of how electricity is produced. (C) Third specific changes in operative logistics processes have to be analysed in order to secure the efficient use of electric vehicles (electric vehicle routing).

Fig. 1: 3E Logistics Concept for Electric Transport

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The addressed scientific problem is the question of identifying all relevant change demands introducing electric road transport systems in operational logistics. And furthermore research in this innovation area is requested to find first solution drafts to be piloted and tested as soon as possible as technology innovation speed will pick up sharply in the coming years. The scientific method is a field evaluation in a logistics company (expert interview, action research, chapter 4) based on the following three research hypotheses: (1) On a macro logistics level existing routing areas have to be redesigned for electric transport routing taking into account specific restrictions as e.g. stop / recharging points, shorter travel capacities, lower travel loads or lower average speed. (2) On a meso logistics level existing routing algorithms and software has to be adapted to new constraints such as e.g. stop / recharging points, travel capacities, lower travel loads or lower average speed. (3) On a micro logistics level existing knowledge of management as well as driving personnel has to be enhanced in order to use the new electric transport systems efficiently and therefore making them profitable as well as sustainable. The suggested research contribution will describe the specific problems and possible solutions for all three levels using example data from DB Schenker daily logistics operations in the region of Duisburg in Germany. The first area of research will be the regional distribution system as it can be assumed that electric transport concepts will first of all be feasible in lower load and distance categories as e.g. goods and parcel collection or distribution to/from regional depots (last mile logistics).

2 Ecological Logistics Perspective Green logistics concepts are in an early stage of development, described by the fact that most of them ascertain a single perspective instead of holistic management views. The term green logistics itself already is a trend in global logistics research and is also present in agendas of companies worldwide since more than fifteen years with the first authors starting to publish from 1995 onwards. Therefore the following literature review is taking into account the last 15 years: Literature in logistics, supply management and supply chain management is in many cases cost driven (Wiedmann et al. 2008), quality (Bogaschewsky et al. 2008) or risk oriented (Goll et al. 2008). Sustainability concepts are to date only implemented as subfactors in concepts within these three specific perspectives or for a specified industry sector (e.g. the food sector; Hamprecht 2005). Even optimization models with a per se integrated approach are missing sustainable parameters in their objectives (Kohler 2008). The following literature survey is describing this in table 1. In this

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structure four perspectives were analyzed if addressed in the selected literature. In order to specify these four perspectives the following description is given: – – –

–

The Operational Perspective is concerning logistics process management, event management as well as routing, scheduling or exception management. The Customer Quality Perspective is a topic in articles concerning customer and industry needs, quality aspects as e.g. low goods damage levels. The Green Perspective is addressed in articles coping with improving sustainability and CSR in general – with topics as e.g. CO2 emissions and energy consumption reduction by transport activities and warehousing. The Logistics Perspective is addressed in articles with the topics like e.g. transport, network and warehousing concepts as well as fleet management, location decisions and concepts aimed at reducing costs and transport times.

The chronological ordered overview below shows that the operational perspective was relatively newly established in green logistics literature. Author(s)

Operational Perspective

Anderson et al. (2009) Krause et al. (2009)

X

Al-Mansi et al. (2008)

X

Customer Quality Perspective

Green Perspective

X

X X X

Archel et al. (2008)

X

Carter et al. (2008)

X

Darnall et al. (2008)

X

Kohler (2008)

X

X

Middendorf (2008) Seuring et al. (2008)

X

X X

X

Straube et al. (2008)

Logistics Perspective

X

X X

Vieira et al. (2008) Koplin et al. (2007)

X

Hamprecht (2005)

X

X

X

X

X

X X

Steven (2004)

X

X

Bowen et al. (2001)

X

X

Rodrigue et al. (2001) Hussain (1999)

X X

Walton et al. (1998)

X X

Fleischmann et al. (1997) Tate (1996) Wu et al. (1995)

Tab. 1: Literature Review Green Logistics

210

X X

X

X X

X


3 Electricity Production Perspective The second concept area regarding electric transport describes the electricity production: As electric transport itself is not necessarily a “green transport solution“ it has to be analyzed how the used electricity is produced. In a “best case solution” all electricity used for transport activities should be produced by regenerative energy modes as e.g. solar, wind or biogas. But as the below depicted development of general electricity production in Germany shows, this is far from the real-world situation: Today Germany is leading with only about 15 % of all electricity production out of such regenerative energy modes. The average for the regenerative energy production in the European Union is only 13,7 % in 2006 according to VGB (2007).

Fig. 2: Electricity Production Development in Germany (Statistisches Bundesamt, Wiesbaden)

It is obvious that innovative concepts for a clean electricity production have to be developed if electric transport should be an integral part of future innovative and sustainable logistics concepts. This would call for localized energy production systems e.g. integrated in logistics sites as e.g. cross docks and warehouses in order to support attached vehicles with electric propulsion systems. But even if a large share of the needed electricity is produced by means of regenerative energies this does not ensure a CO2-free transport: For example solar 211


electricity generation also produces CO2 during the solar panel production. Interestingly this leads to a varying CO2 emissions depending on the location of solar production as fixed CO2 emissions during panel production have to be allocated to the total amount of produced electricity during the life cycle of one panel – and this total amount is strongly dependent on solar irradiation varying heavily in different areas in Germany between for example northern and southern Germany. Therefore specific calculations have to be implemented in order to establish for example which regenerative energy production is suitable – respectively CO2-minimal – in different areas, e.g. wind energy in northern Germany and solar energy in southern Germany.

Fig. 3: Solar Electricity Production and CO2 Emissions in Germany (Lübbert 2007)

4 Electric Vehicle Routing in Practice Within transportation networks electric transport concepts will first of all be feasible in lower load and distance categories, which means within the forerun or the post carriage and distribution (last mile logistics). The figure below shows a typical workflow within transportation networks like groupage or parcel services.

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Fig. 4: Workflow Transportation Network (cp. Vahrenkamp 2007)

Since Transport Management-Software (TMS) for groupage services was introduced about 1980, lots of technical advances were made. The applied logic for short-distance-routing however changed hardly. There are four main steps: 1. 2. 3. – – – – – – – 4.

Routing of outbound shipments based up on five-digit ZIP-Code Routing of inbound shipments based up on five-digit ZIP-Code Routing of inbound shipments based up on five-digit ZIP-Code volume weight time slots freight capacities priorities etc. Picking and loading of shipments by truck driver

The first two steps take place automated in nearly 100 % of all cases. Step three needs a lot of know-how and lots of ‘sense’ for a ‘good’ structure, customers, etc. This is rather difficult to be mapped into a software solution. So in practice this third routing-step is made by managing clerks. They know needs of consignees very well and have an overview about freight capacities, priority shipments, etc. Despite the two automatic ‘pre-routing-steps’ and manual fine tuning by experi213


enced staff, step four is essential for an economic processing. The driver knows his delivery area best and assumes several planning functions. Based up on the ‘prerouted’ shipments he plans his delivery-route. He considers for instance the business hours of different consignees, advised time slots, priority shipments, etc. The driver tries to find his optimal route and loads the shipments in the correct order to assure a smooth unloading. Mostly it won’t be the shortest or most CO2-efficent route compared to a route calculated by route planning software. Today, using combustion-driven trucks, this causes no problems because these trucks have theoretically endless driving capacities resulting from circa 15.000 petrol stations in Germany (see w.A. 2010b). Using electric-driven trucks the range will be limited to a range of about 130 km. Recharging batteries takes lot of time, so even a high amount of recharging-points can only slightly ease this problem. Changing from combustion-technology to electro-technology in metropolitan delivery areas might be rather uncomplicated. Using electric-driven trucks for supplying suburbs, rural or economically underdeveloped areas some modifications have to be made. The following table shows a real-life day delivery route of DB Schenker Duisburg within the Niederrhein area close to the border to the Netherlands. It becomes obvious, that this route hast to be changed for electric vehicles.

Tab. 2: Typical Delivery Route Niederrhein Area (Schenker Deutschland AG 2010, PTV 2009).

4.1 Macro Logistics Level: Redesign of Existing Routing Areas In the presented case it becomes apparent, that a route of about 227 km or 192 km cannot be handled by an electric truck. A redesign of the routing area might be a solution. The table below shows the distances of a roundtrip ‘depot-area-depot’. 214

3E Logistics – Electric Transport Routing City

Roundtrip km

Kamp-Lintfort

46

Alpen

68

Issum

74

Rheinberg

77

Sonsbeck

80

Xanten

98

Kalkar

121

Tab. 3: Roundtrip Main Areas (Schenker Deutschland AG 2010)

Especially the range to ‘Kalkar’ makes clear, that a redesign of the routing area is difficult, because the distance between the Depot and the main areas (post-carriage) is rather long. So lots of the battery-capacity is used for the post-carriage, not for the distribution. To reduce the length of the post-carriage there might be several opportunities. Therefore the number of depots has to be increased. This causes lots of investments and fixed costs. To hold these effects down, it is useful to create an ‘European-setup’ of depots. Today commonly each European country organization has its own depots, which do the post-carriage and distribution in its country. In the present case a dutch depot might be closer to some areas. Another opportunity is the bundling of shipments of different groupagecompanies. This can be modeled on the so called ‘City-Logistik’, ‘Güterverkehrszentren’ or ‘freight-villages’ which were introduced about 1990. For this purpose different freight-forwarders have to cooperate with each other. The main target is to increase the number of shipments for one area and decrease the number of trucks for post-carriage and distribution. In today’s daily business a delivery time of 24 hours from door to door is common. A delivery time of 48 hours or even more is not accepted by the customers. The result for each groupage provider is that they have to operate each receivingarea daily and have no possibility to collect shipments for one area over several days, to get enough shipments to downsize the delivery-areas one the one hand and stabilize or upsize the utilization of the delivery-trucks on the other hand. If customers would accept longer delivery time, this might be another solution for optimization of delivery-routes. It has to be regarded, that this concept determinates the need for higher stock capacities on customers’ sites and even in cross-dockfacilities on service-provider sites.

4.2 Meso Logistics Level: Adapting Existing Routing and Software As mentioned above today it’s common that the route-planning is made mainly by the driver. The driver won’t be able to calculate a route considering the rangerestrictions or even calculate a km-optimised route in mind. The optimised route 215


shown in table 1 clarifies that in this special case a reduction of driven kilometres of about 15 % could have been made. Regrettably in today’s daily business, planning of delivery routes and planning of freight hold are made independent from each other with different software tools. Often this causes a trade-off. To solve this trade-off, the so called ‘Efficent-LoadConcept’ might be a possibility. This method combines delivery route and freight hold planning. It was developed by the ‘Fraunhofer-Institut für Materialfluss und Logistik IML’. The improvement in efficiency is about 25 %. The optimization is eminent for business-models with lots of packing pieces and exceeds the expectations. Therefore it might be the ideal method to optimise delivery-routes. Currently ‘Efficient-Load’ is an approach and shall be integrated in TMS soon, see w.A. (2010a). To maximize the optimization planning software needs lot of information and master data has to be administrated very accurately. In today’s daily business there is often a lack of information. For example the volume or measurements of each shipment is essential for freight hold planning or the ‘Efficent-Load-Concept’. For route planning it is essential to know the business-hours of the customers, delivery time-slots, etc. This information could be integrated into the master data of a TMS. Today this lack of information is compensated by the knowledge of the driver, peering the shipments and planning the route and way of loading. So for future concepts like ‘Efficient-Load” the process of information transport will become more important and the dispatchers have to inform their service-providers ideally via electronic data interchange (EDI). To bring these concepts to perfection, the optimized loading and routing information should be transferred to an electronic guidance system supporting the loading process and overtake the functions of a route guidance system. This guidance system might also replace today’s delivery scanning systems.

4.3 Micro Logistics Level: Enhancing Knowledge of Personnel Depending on current education, knowledge and operational area the personal has to be educated and needs certain knowledge. If the whole process chain is set up on above mentioned concepts it depends on Hard- and Software very strongly and the need of information is of particular importance, otherwise the whole process chain becomes more vulnerable. So every involved person must be educated or provided with information. The figure below shows some examples for knowledge enhancement on different skill-levels.

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Fig. 5: Examples of Knowledge Enhancement

5 Conclusions Altogether from the described research results the following concluding theses can be stated in order to fuel further discussion and enhance practical implementation of electric transport concepts in the context of green logistics: (a) First of all the strategic integration of different management areas has to be observed in order to actually reach green logistics solutions based on electric transport techniques as suggested by the “3E Logistics” concept addressing ecological concepts, electricity concepts and electric vehicle routing concepts. (b) Within each activity area operational concepts have to be developed in order to secure operational excellence in green logistics using electric vehicles. Especially sustainable electricity production has to be established in a local logistics-oriented fashion e.g. by wind and solar installations in logistics sites. (c) Further research is needed in order to test the interdependencies of the explained areas. This should result in real-life CO2 calculations for electric road transport in logistics which is missing up to now. 217


Acknowledgement: This research work is supported by the European Union Regional Development Fund and the NRW Department of Economics and Technology through the Project LOGFOR for the period 2009 to 2012.

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3E Logistics – Electric Transport Routing Klumpp, M. (2009). Logistiktrends und Logistikausbildung 2020. ild Schriftenreihe Logistikforschung, Band 6, 12/2009, Essen: FOM ild. Kohler, K. (2008). Global Supply Chain Design. Estenfeld: CfSM. Koplin, J./Seuring, S./Mesterharm, M. (2007). Incorporating sustainability into supply management in the automotive industry – the case of the Volkswagen AG. Journal of Cleaner Production, 15 (2007), 1053-106. Krause, D.R./Vachon, S./Klassen, R.D. (2009). Special Topic Forum on Sustainable Supply Chain Management: Introduction and Reflections on the Role of Purchasing Management. Journal of Supply Chain Management, 45 (4), 18-25. Lübbert, D. (2007). CO2-Bilanzen verschiedener Energieträger im Vergleich. Berlin: Deutscher Bundestag. Middendorf, K. (2008). Logistik im Spannungsfeld zwischen Globalisierung und Nachhaltigkeit. Baumgarten, H. (Eds.). Das Beste der Logistik. Berlin: Springer, 405-414. PTV Planung Transport Verkehr AG (Eds.) (2009). Map and Guide Professional 2009, Karlsruhe. Rodrigue, J.-P./Slack, B./Comtois, C. (2001). Green Logistics (The Paradoxon of). Brewer, A.M./Button, K.J./Hensher, D. A. (Eds.). The Handbook of Logistics and Supply-Chain Management. London: Pergamon, 339-350. Schenker Deutschland AG (2010). Internal transport data from internal software and authority, Duisburg. Seuring, S./Müller, M. (2008). From a literature review to a conceptual framework for sustainable supply chain management. Journal of Cleaner Production, 16/2008, 1699-1710. Stan, C. (2005): Alternative Antriebe für Automobile – Hybridsysteme, Brennstoffzellen, alternative Energieträger. Berlin/Heidelberg: Springer. Steven, M. (2004). Network in Reverse Logistics. Dyckerhoff, H./Lackes, R./Reese, J. (Eds.). Supply Chain Management and Reverse Logistics. Berlin/Heidelberg/New York: Springer, 163-180. Straube, F./Borkowski, S. (2008). Global Logistics 2015+ - How the world´s leading companies turn their logistics flexible, green and global and how this affects logistics service providers. Berlin: BVL. Tate, K. (1996). The elements of a successful logistics partnership. International Journal of Physical Distribution & Logistics Management, 26 (3), 7-13. Vahrenkamp, R. (2007). Logistik. München: Vahlen. VGB PowerTech e. V. (2007). Zahlen und Daten zur Stromerzeugung 2006, VGB: Essen. Vieira, D.R./da Silva, H. A., dos Santos, A. (2008). Integrated Engineering – The Case of Sustainable Development of Packaging in the Food Industry. Pawar, K./Thoben, K.D./Goncales, R. (Eds.). A New Wave of Innovation in Collaborative Networks. Nottingham: Nottingham University, 325-332. w.A. (2010a). http://www.idw-online.de/de/news361709, date 14.04.2010. w.A. (2010b). www.mwv.de/cms/front_content.php?idcat=15&idart=21, date 14.04.2010. Walton, S.V./Handfield, R.B./ Melnyk, S. A. (1998). The Green Supply Chain: Integrating Suppliers into Environmental Management Processes. International Journal of Purchasing and Materials Management, 1998 (1), 2-11. Wiedmann, H./Teichmann, J. (2008). Next Level Purchasing: Erfolgsfaktor eines aktiven Kostenmanagements. BME (Eds.). Best Practice in Einkauf und Logistik. Wiesbaden: Gabler, 56-65. Wu, H.-J./Dunnin, S. C. (1995). Environmentally responsible logistics systems. International Journal of Physical Distribution & Logistics Management, 25 (2), 20-35. Zelewski, S./Saur, A./Klumpp, M. (2008). Cooperative Rail Cargo Transport Effects, Projektbericht MAEKAS No. 2, Institut für Produktion und Industrielles Informationsmanagement, Essen 2008

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Improving the Efficiency of Rail-Based Hinterland Transport by the Means of Advanced Extended Gateway for Rails

Hans G. Unseld and Herbert Kotzab

Abstract Hinterland is the area over which a sea port draws the majority of its business. Due to the increasing containerization of transport, the hinterland reach of sea ports has been expanded and has thus intensified inter-port competition. As a result of this development, most European container ports now act as gateways to often extensive inland networks. These gateways are nodal points where intercontinental flows are being transshipped onto continental areas and vice versa. In this paper we are going to show how an innovative technological concept for a fast and automatic interface between seaport, inland and hinterland terminals and a novel methodology for interlinking seaports and inland transport flows will improve the efficiency in terms of cost and service benefits for all the involved supply chain partners.

Keywords: Hinterland transportation, network optimization, transshipment, improving efficiency

1 Introduction Hinterland represents the area over which a port draws the majority of its business. It is not always easy to delimit the hinterland of a port, as this term varies with regard to commodity (cf. Bulk versus containers), time or transport mode (see Notteboom 2008). Recent market dynamics do also not allow hinterlands to be seen as an everlasting static concept of ports (Notteboom 2009). The role of seaports and its competition is going to change beyond the emergence of global supply chains, an increasing containerization and importance of transshipment hubs which also impacts the modal split and the congestion in the hinterland of seaports (OECD/ITF 2008 or UNECE 2010). Over recent years sea ports have experienced tremendous growth rates of container handling. Many EU sea ports have seen an annual growth of between 5 to 10% in the last decade (see e.g. Amerini 2008 or OECD/ITF 2008) thus leading to an expansion of the sea221


ports’ hinterland areas (see e.g. Hayuth 1981, Starr/Slack 1995 or Notteboom 2008). As a result of this development, most European container ports now act as gateways to often extensive inland networks (van Klink/van den Berg 1998). These gateways are nodal points where intercontinental flows are being transhipped onto continental areas and vice versa (Nooteboom 2008). The efficiency of seaports to cope with the container flux depends not only on their own processes and available infrastructure and facilities, but also on their connection with the hinterland, notably the efficiency and quality of the inland terminals. The primary function of intermodal inland terminals is to handle intermodal loading units between road, rail or barge, including auxiliary services such as damage inspection and security checks. Roso et al. (2009) have therefore suggested the concept of dry ports that connects the internmodal terminals by rail with seaports. In our paper we further develop the gateway intermodalism concept as suggested by van Klink/van den Berg (1998) against the background of the assumption that an increasing number of intermodal terminals is going to be involved in hub or gateway services which will lead to a growth of rail to rail transhipments of loading units. We also expand the dry port notions of Roso et al. (2009) as we include in our inland terminals also additional services such as storage, agency or trucking, maintenance and repair, electric supply for reefers. As a result, basic and additional inland terminal services involve many different actors and processes. The optimisation of these transhipment capacities, terminal services and processes will greatly improve seaport performance and allow them to grow without further spatial development claims on the local area. In order that the entire distribution system works effectively, these types of inland terminals need to be fully integrated into the supply chain. This is what we call an Advanced Extended Gateway for Rails (AEGR) which are based on innovative automation technologies leading to new terminal design. Therefore we are going to show how such inland terminals can look like and how a fast and automatic interface between seaport, inland and hinterland terminals and a novel way for interlinking seaports and inland transport flows will improve the efficiency in terms of cost and service benefits for all the involved supply chain partners. The paper at hand is conceptual and by taking the Hinterland definition as given by Nooteboom (2008) we will discuss the development of extended gateway concepts from the ports’ perspective. The two key drivers for improving competitiveness are “promotion of effective intermodal systems in order to secure cargo under conditions of high competition” and “increasing their roles in supply chains”. This leads directly to operational challenges, like “to increase of throughput, optimize terminal capacity and make the best possible use of the land”. Furthermore, “the logistics performance and ecology footprint dimension of inland terminals and dry ports are crucial for the further development of hinterland networks and condi-

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Improving the Efficiency of Rail Based Hinterland Transport

tions of high-volume growth” setting clear signals for more rail and intermodal transport.

2 Technology-driven efficiency improvement of hinterland transport Rail transport in Europe has attributes which do not qualify it as a prime source for hinterland transport. The markets respond to rails’ structural, operational and technology shortcomings with low acceptance. As an example, the rail modal split of larger ports in Europe for inland transport in 2008 may vary from < 10% in Le Havre and ~ 10..13% in Antwerp and Rotterdam to ~ 30% in Hamburg and 43% in Bremen. Service and cost competing attributes are in favour for truck transport. Limitations both in ports land use and infrastructure cause traffic congestions which can be compensated for. But environmentally driven restrictions (i.e. particle emissions) are setting limits for even higher shares of truck transport. There are different reasons for the low share of rail transport. A study conducted by UIC (UIC 2006) on limitations in rail infrastructure and terminal capacity in Europe revealed a ~ 20% capacity gap in 2012 with all optimization measures and existing expansion plans realized. The study was based upon traditional intermodal transport processes. A clear need for additional investments in infrastructure and traditional terminals was concluded as being the only rational. New rail production concepts were not part of the study. We propose that that advance in automation and new technologies in physical container handling as a core technology may take a leading role in bridging the capacity gap and creating a significant higher and superior competitive share for the rail mode (ZVEI 2006). Hinterland transport by rail offers promising high potentials for increasing efficiency in cost and time reduction on the one hand and in decongestion of seaports by faster and swifter throughput on the other. In order to reach this goal, shifts of paradigms must be supported, re-organisation must be welcome and the full breadth of new technologies must be applied. The concept presented aims at a cost efficient, competitive and sustainable rail-based transport solution, applicable for decongesting seaports and other rail service production facilities. The main potential for increasing efficiency in hinterland transport lies in the potential of managing the utilisation of high value resources in real time which results in the need to combine most efficient technologies in industry with state-ofthe-art control strategies. The technologies for material flow include automatic handling and storing of all types of containers with controls at every stage of the gateway, and interaction with a novel type of train between seaport shore and gateway. Standard trains between gateway and hinterland terminals and conventional trucks serve as per demands. The utilisation implies the optimal usage of all capacities for producing transport services in both directions (export and import) according to the cost and service level agreed. Methods and tools for managing assembly lines and factories (i.e. for managing OEE, Overall Equipment Effective223


ness) help to keep non-productive time at a minimum level. From our point of view, the following areas of technologies, processes and planning issues offer efficiency improvement potentials: – – –

–

–

Automation of handling technologies for rail loading and intra-terminal transport of containers; Real time controls and automation of the complete gateway assure its full integration into supply chains; New, though already proven solutions for this type of application, such as automatic block storages as buffer stores and semi-automated truck loading facilities; Operating high performance trains with novel (certified) high LCC rail wagons with additional features for fast operation and further means for high utilisation of loading length; New planning, control and management paradigms including the transfer of supply chain and industrial process know how into a new vision for rail and especially intermodal transport.

3 Inovative concept of a rail gateway for seaports and hinterland transport 3.1 Rail transport as an answer to main transport related problems at seaports One of the main problems of today’s seaports container operations and also the main obstacle for further growth are the limitations of spatial dimension with regard to size, configuration and geographically preferred position. Since European seaports are mostly connected with large cities, traffic congestions and environmental restrictions put further limits on the growth of seaports container volumes. Hinterland or “dry port” solutions are now being reviewed and considered by many port organizations as option for further growth and at the same token as answer for enhancing their competitiveness (Roso et al. 2009, Visser et al 2009). For improving the integration of rail transport, we suggest the rail technology AEGR (Advanced Extended Gateway for Rail) which is a version of an extended gateway, embarking latest technologies for a best fit interface of rail transport operation towards the hinterlands rail network. An AEGR describes an inland terminal which consists basically of all non-seaport operations at a location off the seaport terminal and in which both are interconnected with a high performance rail transport system (see Fig. 1).

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Fig. 1: Concept of an Advanced Extended Gateway for Rails

An AEGR is an inland terminal consisting of all non-seaport operations at a location off the seaport terminal and in which both are interconnected with a high performance rail transport system, see figure 1. The functional border shown determines a first suggestion on the scope of a future seaport terminal. In this concept the following main concerns for seaport gateway and extended gateway concepts are addressed and cost efficient solutions suggested: –

–

–

–

Land use at shore by moving a large, yet flexible amount of containers to a less expensive land. Transport restriction become less burden for expansion of ports. Congestion at seaport vicinities by applying a new paradigm: a) moving a maximum share of volume off shore area to an AEGR by rail and sort, handle and load it there to appropriate modes, like truck, barge or rail and b) by using high efficient rail transport in its best manner off shore and within the seaports range of responsibility. Environmental aspects for Hinterland transport by shifting main volumes to rail transport: a) performing all rail transports between shore and AEGR with ecological, cost efficient, high LCC and silent trains and b) when starting and ending the transport at seaport terminals by rail also a higher share of the main haul is expected to be transported by rail. Competitiveness of seaport by integrating one or more AEGR’s within an existing rail infrastructure network at places of transport network capacity disruptions in its preferred Hinterland. This will lead to: a) higher utilization of trains per track, b) more tracks per network leg, c) more flexibility in real-time scheduling, d) flexibility for investors and operators, e) higher profitability for the seaport with its Hinterland.

225


The main transport means for this concept within the seaports authority is RAIL transport for twofold reasons: 1. the throughput of the container flux and the speed of total transport of an arbitrarily selected ITU by use of trains with maximum cargo capacity and high operation productivity on existing rail infrastructures, and 2. costs of rail transport and option for automatic handling and flexible loading of the flux of containers.

4 Spatial separation of seaport terminal facilities The two areas are separated according to their main operations and best suited location for highest performance according to their strategic goals: –

–

Seaport operations are performed in an area with all ship to berth/shore, and store operations as well as such ones which support directly these vessel-driven time-critical processes and a loading zone for both standard and shuttle trains, Inland terminal operations are performed at an inland location: all remaining auxiliary services, including storage, services to intermodal transport and a high performance loading zone II with automated transloading functionality and integration into the intra-terminal transport network; overlap does exist with seaport operations at rail loading and container management functions.

Both locations are being interconnected by highly efficient rail transport lines on existing rail infrastructures. The functional borders embracing the AEGR are shown in figure 1 as dotted-line. It enfolds all processes needed to perform the rail based functions for serving the hinterland transports. Earning the full benefits from an advanced extended gateway set-up requires a split of the buffer stores into one part at sea side (Buffer store I) and another at the AEGR (Buffer stores II). The seaport buffer store serves the shores import and export demand by classical transport means (i.e. van or straddle carriers, AGVs, trucks and tugs). Contrary to that, the buffer store at AEGR serves incoming and outgoing trains, as well as trucks and other external services, like barge loading or LSP located outside the gates of an AEGR. An automatic intra-terminal transport system interconnects the buffer store with the rail and road loading and the external users.

5 Transport and logistics functions of the AEGR The core function of an AEGR is the service of the ship-to-shore loading processes with the container volume flux needed according to the shores demand for export and import containers. In a kind of time slot operation, this key function is shared among the individual terminals according to their demand and organized omnidirectional for serving the distribution network in the hinterland according to import containers requirements as well. An off shore buffer store with arbitrary access 226


to any container with a capacity of 25 to 40% of its present capacity should serve a peak demand balance. This means that the process for handling high volume fluxes goes in both directions: Import and Export and their relevant imbalances. Further functions include the following primary services (see also Fig. 2). These services shown are performed automatically in a 24/7/365 hours mode and are expected to be very fast, cost efficient and remotely controllable: – –

– –

–

Rail shuttle transport service between seaport loading zone I and AEGR loading zone II for providing sorted flux of containers between shore and Buffer II; Train loading service starting and ending at AEGR loading zone II to hinterland destinations for providing flux of containers between AEGR and hinterland terminals; Loading service of containers to direct trains travelling from seaport terminal to hinterland terminals as “stop-load-go” operation for utilisation reasons; Container storage service in buffer store at AEGR and intra-terminal transport to auxiliary service providers with additional actors involved: container damage inspection and container repair and maintenance and further services, i.e. electricity supply for reefer; Truck loading service for every container within the AEGR and transport service to external sources, i.e. barge loading stations.

Fig. 2: Options for transport and services of an AEGR

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All train loading processes at AEGR are performed as an automatic operation, all buffer stores and intra-terminal processes are performed the same way and all truck loading processes are performed as a semi-automated operation. For the first time, this type of service is suggested within a hinterland scenario, based upon the development of the novel automatic transhipment system for loading trains below the catenaries (Unseld 2008). This technology solution was never considered before and seems to be ideally suitable for further research towards integration of rail operation and logistics, in particular hinterland transports (Kotzab/Unseld 2008).

6 Design and architecture of a process-oriented AEGR The design of an Advanced Extended Gate way for Rail is mainly determined by the throughput and flexibility requirements of the material (container-) flow between shore and gate “Entry of port”, to be handled in both directions, import and export. In an ideal case, the need of the seaports’ shore operations determines the export flux, whereas the distribution networks demand determines the import flux. Both fluxes should meet at clearly determined conditions at shore for optimal handling of the vessel at berth at lowest cost and/or highest loading performance. In an AEGR, dislocated buffer stores and other means of managing the flux into all directions are core elements for this kind of performance. Such a terminal design is not known so far and a first version of process-oriented architecture of this type of an AEGR with a split of operations at two locations is shown in Fig. 3. Se aport terminal fa cilities FUNCTI ON -ORIENTED B ORDE R OF SEA PORT AND I NLAND TERMINAL

Advanced Extended Gateway for Rail Seaport operations

Inland terminal operations SP 1 SP 2

(hinterland location)

SP n

…..

Buffer Store

Buffer Store

(berth or sea port location) In tra- te rminal trans port

High efficient rail transport

Seria l load ing proce ssin g

Shore to store

L ogis ti cs Servi ce P ro viders

C ontain er L oadi ng and Sortin g Area

„Entry of Port“

Seri al truck l oadin g proc essi ng

C ontai ner Loadi ng and Pro cessi ng Area H ig h performance pa ra lle l proces sing

Serial and paral lel process ing

ID of IL U

Tra nsport , s ort, store and l oad proces ses

Shuttle tran sport proces s

Loa d , sort, store and in tra termi nal transp ort proc esses

Harbour Port Gate

Fig. 3: Process oriented architecture of an AEGR

228

Gate

External conn ection to intra termina l transpo rt proces s

Train pas sing p ro cessi ng Servic e proce sses

Entry and exi t process es

Termi nal manage ment a nd interna l a nd externa l i nter fac es


In the case of one AEGR serving more than one seaport terminal, their operational facilities are split accordingly, whereby each one is served by its high performance rail transport lines respectively and the container loading and sorting area at AEGR handles all of them. This type of AEGR will feature one main gate at the ‘Entry of Port’, plus a ‘Harbour port gate’ at each of the seaport terminal location. The terminal management function contains all elements necessary for a flow-oriented and automatic operation and control, easy to integrate into a transport supply chains. The process oriented architecture allows an efficient, seamless and to-the-pointof-action transport between shore to store function and the gate at ‘Entry of port’. The above figure shows the basic structure interconnecting two locations by highly efficient rail transport. It seems feasible to design more complex structures with three and more locations as well, and to interconnect them by shuttle or full load transport trains or by local truck service providers. According to an initial process analysis, all four core functions (storage, loading trucks and trains, transport) were split according to their transferability for performance at the best suited location within an AEGR, either at seaport or hinterland location. The criteria for transfer are mainly determined by their strategic objectives, such as: total productivity of seaport facilities, investment options, congestion issues and environmental considerations.

7 Consequences of the AEGR on modal shift Today, transportation between seaports and hinterland consignors/consignees is mainly performed by trucks for the simple reason of costs, flexibility, handling efficiency and provision for supply chain integration. In order to challenge this strong position with a competitive rail offer and to trigger an increasing share of rail mode, the supply chain using rail transportation has to improve significantly for handling these volumes. The basic strategy of working with an AEGR concept is a significant shift of container volumes to rails in the vicinity of seaport terminals for all reasons described. Fig. 4 illustrates this strategy as a 10-years scenario with development of container volumes by modes, handled by seaport terminal facilities. In this scenario, the present status quo calls for a truck transport share of app. 70%, with both co-modes rail and barge holding at approximately 15% each. The following mode share and volume assumptions will be applied: –

–

Status quo volumes and their share of modes mark the starting point of the scenario (Rail 1). The actual rail transport volume is determined to a great extend by the rail infrastructure capacities available. All growth-induced volumes are transferred to rail mode (as of the seaports operating gate). This is subject to two new AEGR-types of service: a) an efficient rail shuttles and b) close to full direct trains with “stop-load-go” services at AEGR. Some extension at bottle necks within the present rail infrastructure be229


–

–

tween seaport terminals and inland part of AEGR still exists, big investments can be avoided. Rail transport share at seaport is growing up to volumes high efficient rail stems (Rail 2). Growing volumes over times may require some more investment in rail infrastructure and AEGRs. It seems however, that the level of investment into general purpose rail infrastructure (suitable for passenger and for freight transport) can be reduced to the advantage of a more dedicated investment for boosting the logistics performance of rail freight transport. AEGR operates as an inland terminal with volume sharing between truck and rail mode (Rail 3). The concept of AEGR includes a very flexible, powerful and competitive modal shift facility for serving trucks at their discretion. It seems realistic that this type of facilities will be accepted by the logistics service and trucking companies’ right from beginning.

The total scenario calls for rail as main haul handling close to 50% of hinterland container transport: there is no smarter way to shift significant volumes of containers on rail.

Fig. 4: Modal split of hinterland transport with AEGR as 10-years Scenario

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Keeping this scenario in mind, AEGR concepts can meet the key objectives for future planning of seaport expansion in the following manner: –

–

–

Seaport congestion on roads is reduced by moving a higher share of truck transport to the inland terminal; since this option is highly cost attractive, a higher share of road transport will shift and decongest the port. Rail transport capacity is increasing by real time utilisation management of high performance rail and rail-to-rail operations in 24/7/365 hours operation modes. The buffers plugged into transport chains will balance the network utilisation. This will lead to higher capacities made available for the total transport chain. The sorting facility produces higher differentiation of destinations; hence more hinterland terminals may be served with higher degree of service. Seaport efficiency is improving by extending operations management for seamless automatic physical handling of containers across the supply chain, especially in inland terminals; according to user requirements this will be made possible with regard to real time, over a larger transport supply chain, as well as to volumes, time horizons and management strategies.

8 Conclusion and outlook Increasing volume at European seaports put pressure on the hinterland transport infrastructure leading to congestion (OECD/ITF 2008). In order to solve this issue, we have proposed in this paper to expand the notions of gateways and intermodalism in form of network shaped port hinterland as suggested by van Klink/van den Berg (1998) by introduction the concept of AEGR. With our proposal, we are able to strengthen the hypothesis by van Klink/van den Berg (1998) who proposed that “gateways are in an excellent position to stimulate intermodal transport..” (p. 8). Rail terminals using the loading technology described have the potential of bringing about high efficient container handling by integrating the rail loading operation into the logistics processes of a seaport sourced transport chain. Future seaport terminals will benefit from their function in their strategies of improving their hinterland competitiveness, their environmental performance and their role as regional driver for sustainable development. Any ground breaking new technology has to prove its value to their end user by adding significant higher value. Especially in asset rich and long term oriented environments, like rail transport short term benefits traditional issues play a role as well (Engelmann 2003). Therefore, transparent commercial and operational considerations being the ‘entrance fee’ for transport logistics operators to get interested. For a number of research fields, new challenges emerge. As an example the operational regime of integrating rail into seaport operations expects advantages from this new kind of ‘Hinterland-Hub’ (Schönemann 2010). The utilization of AEGR in 231


the hinterland of seaports would also increase their supply chain competitiveness (see de Langen/Chouly 2004). The actual trend in transport network development supports networks with flexible nodes in a large regional dispersion (Nooteboom 2009). One of the technology challenges is to design and develop an intra-terminal transport system on rail for cost, performance and environmental reasons; this opens a new wide field for advanced active heavy load transport technologies (Unseld 2009). Another area for research is the ‘last mile’ issue as part of the hinterland logistics (Rodrigue 2008) as well as the coordination of the hinterland transport chains (see van der Horst/de Langen 2008). Applying these new technologies in that field would stimulate an affordable main modal shift to rail transport. To make this happen is probably one of the greatest challenges transport technology offers right now.

References Amerini, G. (2008): Short sea shipping of goods 2000 – 2006, Statistics in focus, Transport 2/2008, European Communities, 2008, ISSN 1977-0316. De Langen, P.W., Chouly, A. (2004): Hinterland access regimes in seaports. European Journal of Transport and Infrastructure Research, 4, 4, 361-380. Engelmann, J. (2003): Zielorientierte Forschung und Entwicklung für den Schienengüterverkehr. Schriftenreihe A des Instituts für Land- und Seeverkehr, Berlin:Universitätsverlag der TU Berlin. Hayuth, Y. (1981): Containerization and the load center concept. Economic Geography, 57, 2, 160-176. Kotzab, H./Unseld, H.G. (2008): Fast Transhipment Equipment and Novel Methods for Rail Cargo, in: Kersten, W., Blecker, T. & Flämig, H. (eds.): Global Logistics Management, Berlin: Erich Schmidt Verlag, 393-403. Notteboom, T. (2008): The relationship between seaports and the intermodal hinterland in light of global supply chains, European challenges. Discussion paper No. 2008-10. Paris:OECD International Transport Forum. Notteboom, T. (2009): The role of dry ports in logistics towards a terminalization of supply chains. Contribution to ‘Site assessment’ conference in the framework of the Interreg North Sea project ‘Dryport’, Bruges. OECD/ITF (2008): Port competition and hinterland connections, Discussion Paper No. 2008-19, Joint Transport Research Center, Round Table, 10-11 April 2008, Paris. Rodrigue, J.-P. (2008): Transport Trends and Inland Hubs. Contribution to 3rd European Conference on Inland Terminals, Paris. Roso, V., Woxenius, J., Lumsden, K. (2009): The dry port concept: connecting container seaports with the hinterland. Journal of Transport Geography, 17, 338-345. Schönemann, R. (2010): Schienengüterverkehr an der Schnittstelle zum Seeschiff. Internationales Verkehrswesen, 62, 4, 30-35. Starr, J.T./Slack, B. (1995): Ports as gateways: a traditional concept revisited. Proceedings of the 5th Conférence Internationale Villes et Ports, pages 89-96, AIVP, Dakar. UIC (2006): Developing Infrastructure and Operating Models for Intermodal shift, DIOMIS, Final Report: Work package 11: “Report on Combined Transport in Europe 2005”, Paris: UIC. United Nations Economic Commission Europe (UNECE) (2010): Hinterland connections of seaports, United Nations, New York, Geneva.

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Improving the Efficiency of Rail Based Hinterland Transport Unseld, H.G. (2008): Das EU-Projekt „FastRCargo“. Moderner Schienengüterverkehr, Bahntechnik aktuell, 18, 2-15. Unseld, H.G. (2009): Neue Logistikkonzepte für den Containerumschlag am Standort Hamburg, Advanced Extended Gateway for Rail. Contribution to 5th Hamburger Hafentag, Hamburg. Van der Horst, M., De Langen, P. (2008): Coordination in hinterland gransport chains: a major challenge for the seaport community, Maritime Economics & Logistics, 10, 108–129. doi:10.1057/palgrave.mel.9100194. Van Klink, H.A., van den Berg, G.C. (1998): Gateways and intermodalism, Journal of Transport Geography, 6,1, 1-9. Visser J., Konings, R., Pielage, B.-J. & Wiegmans, B. (2009): New Hinterland Transport Concept for Port of Rotterdam: Extended Gateways with Innovative Connecting Transport Systems. Contribution to Transportation Research Board 88th Annual Meeting, Washington DC. ZVEI (2006): Technologie-Roadmap Automation 2015+. ZVEI, Frankfurt

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Evaluation of Telemetry Implementation Benefits for a LPG Distribution Company

Abdelkhalek Nakabi and Zitouni Beidouri

Abstract Orders quantities are an essential input to routing and scheduling models. However, in LPG (liquefied petroleum gas) distribution real life cases demand is hard to determine precisely at the moment of delivery planning. This is simply due to the fact that gauge levels continue to decrease since the ordering date, when customers communicate it at the first time. The second reason is that customers may have their ones reasons not to communicate the right gauge level information. Also many customers forget to check their tanks and then are obliged to make urgent orders. This has effect on transportation performances and customer satisfaction. We assessed for an LPG bulk distribution Moroccan company the impact of this non-deterministic demand on transportation key performances, such as On Time In Full Rate, Drop size average, trucks utilization and stocks breakdown and compared it to a simulated planning method using telemetry technology to get accurate gauge level data at the customer premise. This comparison showed very important potential performances improvement if this technology is efficiently implemented and process supported to feed planning and scheduling processors.

Keywords: Telemetry, customer inventory management, cost of poor quality, six

Table of abbreviations LPG: Liquefied petroleum gas COPQ: Cost of poor quality GSM: Global System for mobile communication GPRS: General Packet Radio Service SMS: Short Message Service ERP: Enterprise Resource Planning

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Abdelkhalek Nakabi and Beidouri Zitouni

1 Introduction Today, sensors and wireless communications along with the business insight they generate are delivering measurable business benefits. But few organizations have tapped fully into the enormous potential they can offer. The technology we assess is related to the use of LPG tanks telemetry in customers’ premises. Essentially gas distributors, for which gains related to logistic optimization are very significant, have been intensifying their investments in technologically innovative solutions, namely in telemetry systems that will allow them to know the amount of gas in each tank, as well as each customer's consumption, at distance. The market of telemetry technology is then booming in Europe and US. In developing countries such as morocco, this started to be used just in the last few years in some multinational distribution network. This paper objective is to measure the benefits of a telemetry solution for one of the most critical distribution network that gathers many constraints. This paper is divided into three major parts. In the first one we propose an introduction to LPG telemetry and a proposal of a telemetry solution the studied company could have used. The second part objective is to introduce the concept of Costs of Poor Quality (COPQ) and define some that allow assessing the benefits of the solution implementation. The objective of these COPQ’s introduction and monitoring is to truck the cost and customer satisfaction effects of the non-deterministic demand and then define saving opportunities the innovative project should deliver. In the third part we will presents result of these observation during a period of six months prior to the project implementation and one year further mainly assessing benefits related to COPQ reduction compared to the saving opportunity detected in the project business case. Many aspects of this project management are out of the scope of this paper such as technical implementation aspects and constraints the company faced during this journey. Also we didn’t go into details in software and hardware description of the proposed solution, as this wasn’t our primary focus.

2 Distribution company overview The company we studied is a local LPG distribution company (part of a multinational company). We are interested in this paper to the LPG bulk distribution. The packed LPG is not taken into account. The company distributed in 2008 was about 40.000T using a fleet of 9 and 3 trucks of 17 tons capacity respectively. The distribution network involves 1 supply point and 450 customers. LPG is stored in tanks located outside the customer’s buildings. To ensure that an adequate supply of LPG is available to the building, each tank must be periodi236

Evaluation of telemetry implementation benefits for a LPG distribution company

cally refilled by a LPG delivery to the tank location. LPG orders are placed to the distribution that makes the deliveries utilizing tank trucks.

3 Telemetry solution objectives The experience of the studied distribution company demonstrates there are differences between the actual gauge level at the delivery moment and the mentioned level when ordering. These differences are due to: –

– – –

Consumption evolution between the order time and the delivery time as the customer continue to use product between the two events. The history of the consumption curve of the customers could help in reducing these differences but as we don’t usually face a regular consumption rate, the need for a deterministic method such as telemetry still accurate. Misreading of the gauge level by the customer. Some ordering stockmen are not on delivery site and just estimate the gauge level, as they can’t move to the remote sites frequently. Some customers try to prevent stock-out by giving a false gauge level to urge the delivery. This can be explained as a result of mistrusting the reliability of the delivery service.

The company aimed then to introduce a telemetry system that replaced the existing solutions, and ensure demand accuracy and better customer retention. The primary aim is to reduce the gaps between the ordered quantities and the actually available drop capacity and hence improve transport performances, customer satisfaction and deliveries reliability. In addition to improving distribution performances, the solution also will provide data regarding customer consumption and gauge level information that will allow trips to be planned efficiently and truck usage optimised. This is possible by using the telemetry system to automate the collection of customer information associated with its LPG consumption. This capability can be expanded on in the future by incorporating the monitoring of additional tanks information, e.g. temperature, leakage detection, through use of the functionality available from sensor engineering. Automatic LPG reordering systems avoid the consumer's inconvenience of periodically checking the gauge level. In addition, by utilizing this system, the delivery planning is more efficiently and competitively performed. Such reordering system detects when the gas reaches a particular level and, upon detection, transmit an informational message, via a telecommunication channel to the distributor. By knowing when and in what quantity a consumer requires LPG, the distribution company may more economically schedule the deliveries to the customer. In gen-

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eral, deliveries will be made only when a consumer requires a substantially full tank-load.

4 Solution description Telemetry is then the remote measurement and collection of data, such as meter reading, tank level monitoring or environmental monitoring. Telemetry is typically used to gather data from distant, inaccessible locations, or when data collection would be dangerous or difficult for a variety of reasons. For LPG distribution business a typical solution could resemble to the descriptive figure below.

Fig. 1: Telemetry solution architecture proposal

The proposed solution comprises the four main functional blocs described and depicted below. The LPG tank sonsor:

LPG systems have more demanding requirements than fuel oil systems. LPG tanks and LPG gauges, which are attached to the tanks, are located outside buildings. Consequently, LPG gauges must withstand extreme environmental conditions. In addition, because LPG is stored under pressure and is highly explosive, a LPG system must ensure that the gas does not leak or inadvertently flow into the building.

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A stuck valve or gauge can result in catastrophe. The LPG sensor must be able to meet these same stringent demands and not add any risk of leakage or explosion. GSM Telemetry device: The GSM & GPRS Telemetry products have been created as universal wire free monitoring devices that work across the mobile phone networks. The wireless telemetry devices can send alarms by text message and email, they can send regular reports and they can interface to web based data acquisition tool, Gateway, for historical reporting, graphical data presentation and interface to I.T. systems and ERP Back Office Serve: The main telemetry solution repository managing both thanks related reference data (e.g. depot, customer, tank size, consumption curve, product, minimum and maximum stock level) and gauge current data to/from ERP as well as managing the synchronising of data to web interface. Web & Telemetry Management Server: Provides the depot staff and customer with stock level status and consumption curves and allows messages be sent to/received from stakeholders. It also manages the configuration of the GSM telemetry devices, in terms of message sending frequencies, and stock level updates; Interface to ERP System(s): Uses XML to provide a single interface to external stock management, supply forecasting, planning and scheduling modules. The XML files containing reference and planned transactional data from ERP are placed in a file share and are imported into the telemetry System. Recorded transactional data is returned to ERP via a second file share.

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5 System Architecture & Data Flows

Fig. 2: Telemetry functional architecture and data flows

The proposed telemetry solution components provide the functionality: –

– – – –

to enable the mobile/fixed communications (via GPRS/GSM, Dialup, LAN, WLAN) and data synchronisation between telemetry server and the telemetry device; to manage the telemetry device configuration definitions; to enable remote management of the telemetry application upgrades and configuration; to produce/handle XML interface files to/from ERP; to provide company staff and customers access to gauge level status and product consumption evolution;

6 The Cost of Poor Quality (COPQ) Concept The business case for the telemetry implementation rests on the improvement of transactional and distribution costs, coupled with improved customer service and retention levels. As there was significant future upside from operating a business with a more accurate demand forecasting, and lower costs, calculation of these benefits have been factored into the business case. The benefit assumptions calculations assume that the existing customer and volume base can be served at a lower cost and more effectively (resulting in improved customer retention) if the waste 240


and failures related to the non accuracy of gauge level at customer premises can be taken out of the existing process. The identification of COPQ elements results from both business experience and use of the Ishikawa diagram process and XY matrix mapping of route causes for defects (from the Six Sigma toolkit). The COPQ is not all removable from the process and only a percentage will be fully realized. This realizable value is termed the Project Prize. There is also the cost of achieving this more efficient process (the Cost to Repair, which is a one off cost) and an additional cost of maintaining it (Cost to Control, which is ongoing). Furthermore the cost of repair will increase at a higher rate, the higher the level of COPQ to be removed from the process. The COPQ principle reflects all cost that would not have been expended if the quality were perfect. In general, COPQ includes the cost involved in fulfilling the gap between the desired and actual product / service quality. It also includes the cost of lost opportunity due to the loss of resources used in rectifying the defect. This cost includes all the labor, rework, disposition, and material that have been added to the unit up to the point of rejection. For the case of LPG distribution, we take into consideration costs of poor quality related to demand accuracy. To determine the saving opportunity related to these cost a six months sample was considered to evaluate the ordering and delivery process prior to the telemetry project implementation. We made the assumption that the saving opportunity is equal to the aggregation of the COPQs affected by the ordering non-accuracy assuming that as the distribution network, distributed volume and other planning and scheduling remained unchanged the only benefits root is the implementation of the telemetry solution. Other COPQs than those related to reordering system were not taken into consideration. Prior to the presentation of these COPQ evolutions we will next define the chosen ones and the calculation methods.

6.1 Non-deliveries: A non-delivery is where a delivery has been planned and the customer visited, but no product was delivered. This could be for various reasons, such as tank full, gates locked, customer not present etc. In order to effectively measure the rate of non-deliveries we need to record the total number of orders that were visited but not delivered. And express this as a percentage of total number of deliveries during the sampling period. The main elements of waste are as below: Additional trip distance: When we attend a customer site with the intention of delivering, but are then unable to do so, the distance taken to do this is waste. For this we should measure the 241


planned Km's of the trip, including the non delivery minus the planned Km's of the trip without the non delivery resulting the Km's wasted for the non-delivery. Additional Trip Time (Hrs:Min): When we attend a customer site with the intention of delivering, but are then unable to do so, the time taken to do this is waste. Planned Time of the trip, including the non-delivery. Minus the planned Time of the trip without the non-delivery. Equals the Time wasted for the non-delivery. Additional transaction time: (Where Non Deliveries are not visited) There may be cases where deliveries are cancelled after the trip has been planned and cleared for execution. In this case we have a non-delivery, where the customer has not been visited. In extreme cases where this is it may be necessary to measure this effort and incorporate the cost of the additional transaction time.

6.2 Urgent Deliveries: It’s a delivery that is expedited through the trip planning process after the original trip has been completed and passed for execution. It is not necessarily just an order where the customer is nearing stock out and therefore needs a delivery urgently. Any Order/Delivery that is added to a tour once it has been 'printed' (Sent for delivery) in the ERP system." In order to effectively measure the rate of urgent deliveries we need to record the total number of orders expedited through the system, after the planning is complete. And express this as a percentage of the total number of orders delivered. This should be collected at trip level. The main elements of waste are as below: Additional Trip distance: When an urgent delivery is expedited through the system it may mean that additional Km's are taken in the trip as a result of fulfilling this order. If this is the case then the Km's taken can be seen as waste. If the Km's taken is less than planned then there is no COPQ of Km. Actual Km's of trip minus the planned Km of the trip. The Delta here is our waste. Additional Trip Time: When an urgent delivery is expedited through the system it may mean that additional time is taken in the trip as a result of fulfilling this order. If this is the case then the time taken can be seen as waste. If the time taken is less than planned then there is no COPQ of time. Actual time of trip minus the planned time of the trip. The Delta here is our waste Time to rework: Another clear element of waste is the time taken by the planner to rework the schedule to accommodate the urgent order. Average time to replan a trip with urgent delivery multiplied Planner cost per hour.

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6.3 Drop size: Many of deliveries occur before they are really needed. I.e. when the stock is above the optimal replenishment point. (20 - 25% gauge level). It is also the case that deliveries sometimes do not replenish the stock to the maximum level possible. (85% of the tank capacity). In both of these instances we have a small drop size, which doesn't make the most of the opportunity afforded by the size of the tank or stock holding. To generate the baseline of performance we need the following data, Initial percentage at delivery / stock level as a percent as total stock. Size of the tank / Total stock holding capacity. Quantity delivered. In order to make the calculation we also need historical data to form an idea of what the potential saving may be - Stratified by tank size, Number of deliveries over 1 year, total volume delivered over 1 year.

6.4 Vehicle Utilization: Vehicles are some of most expensive assets and as such we need to ensure that they are fully utilized. If a vehicle is only utilized at a rate of 50%, it is fare to say that the other 50%, unutilized capacity is wasted opportunity. For every 2 tours done by that vehicle, there should only have been 1, in this case every other tour is COPQ. It is, however, unreasonable to assume that 100% utilization is possible at all times. The global standards have been set in recognition of this, where Bulk vehicles should reach 93% utilization and Packed Vehicles 85%. The utilization of a vehicle is expressed as a percentage of its utilized capacity. The basis of the COPQ calculation is the number of deliveries and therefore trips that could be saved, if the fleet were to be running at the expected standards. Total volume delivered divided by vehicle capacity time multiplied by 100 equals the percentage utilization for a tour.

7 Saving opportunities and COPQ reduction tracking We tracked for the company these poor quality indicators to support the project business. A six-month observation period was performed by the company and considered as sufficient sample of the distribution reality. The tracking of these costs showed a total saving opportunity of DH 1.6 million (local currency). The evolution during the project implementation period of these costs is not represented in the charts below, as it not fit for the purpose of this paper. Other reason why we don’t consider the transition period is that during the implementation of this project, remote sensors reported inaccurate gauge level and the reference data in the central server needed to be tuned to get benefits from the solution. So we plotted only the project posterior cumulative COPQs reduction compared with the detected saving opportunity related to each poor quality as a result of the project prior observation. 243


7.1 Non deliveries: More than 76 planned drops were not delivered during the period prior to the project implementation resulting in 170 kdh of extra cost. As the observation period was about half a year the saving opportunity is equal to twice the cost. The average delivery cost is about 2.2 kdh. During the period of one year after telemetry project implementation only 16 non deliveries were registered and yet were not related to ordering process but due to other reasons, mainly customer absence, or technical issues. The saving opportunity was then seized at 90 % during the full year.

Fig. 3: Non delivery related COPQ cumulated saving vs. initial opportunity

7.2 Urgent deliveries: The extra cost related to urgent deliveries for the six months prior to the project implementation was about 127 kdh resulting from 59 urgent deliveries. The detected opportunity related to this is estimated to be about 260 kdh. This opportunity was exploited at 80 %. The residual non-quality is due to credit issues as some customers come into emergency or stock out because of non-payment matters.

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Fig. 4: Urgent deliveries related COPQ cumulative saving vs. initial opportunity

7.3 Drop size: The waste related to deliveries drop size was estimated to 920 kdh per annum at the beginning of the project. This waste was reduced to 380 kdh. Other efforts remain to be deployed to optimize planning and scheduling methods, to review tanks capacity to seize fully the identified opportunity. But still the gain obtained in term of drop size improvement (with moved prom 5.4 T per drop to 6.7 T per drop) is one of the most important. Others aspects of this gain were noted by customers as the number of truck visits were reduced by 20%. The number of saved tour is about 246 tours equivalent to 75000 km distance travel.

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Fig. 5: Drop size related COPQ cumulative saving vs. initial opportunity

7.4 Truck utilization: By having a continuous on line view of the available customer capacity in one zone, trucks can be filled at maximum capacity when making a tour and profit can be looked at by gathering as much as deliveries in one tour. To do this, only competent planning team can get value from the gauge level knowledge the solution gives. Also, by extrapolating the consumption curve, planning workforce can easily optimize the delivery start time to have maximum orders fulfilled at one time. The estimated opportunity related to truck usage was fully seized which paid back 920 kdh during one year with equivalent to a reduction of the fleet size by 2 trucks during one year.

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Figure 6: Trucks utilization COPQ saving vs. initial opportunity

8 Conclusion In this paper we assessed one of the most booming technologies in LPG distribution effect on a distribution company we worked with during a period of 3 years. Other tanks and customers parameters such as temperature, gas leakage and technical issues are currently considered to be remotely reported using the same support to give a complete solution to the company and it’s customers. This can be subject of further papers. Many other others aspect of this project were looked at during this period. Such as, implementation technical constraints, humane resources change impact, network, sensors, radio troubleshooting and software engineering. A multi disciplinary research team still working close to other companies to assess analyze and help to deploy new technologies to the logistics practices in morocco. This demonstrated that IT applications would be during the next few decades an important elevator of logistics, supply and distribution management.

References Reducing the Cost of Poor Quality Michael Cieslinski Panasonic Factory Solutions Company of America Buffalo Grove, IL 847-495-6100 Lean Six Sigma Demystified by Jay Arthur McGraw-Hill © 2007 Lean Six Sigma for Supply Chain Management—The 10-Step Solution Process by James W. Martin McGraw-Hill © 2007 Implementation of Six Sigma: Smarter Solution Using, Statistical Methods, second edition, by by Forrest W. Breyfogle III Copyright Forrest W. Breyfogle III © 2003

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Abdelkhalek Nakabi and Beidouri Zitouni Supply Chain Vector: Methods for Linking the Execution of Global Business Models With Financial Performance by Daniel L. Gardner Copyright J. Ross Publishing, Inc. © 2004

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IV. Performance Enhancements in Modern Supply Chains

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A Genetic Algorithm of Supply Chain Performance Analysis, Focusing on Information Delay

Asadollah Najafi, Abbas Afrazeh, Heinz Bartsch

Abstract Supply chain management (SCM) is a major component of competitive strategy, with direct implications on organizational productivity and profitability. Beside, supply chain (SC) delay is a critical factor in SC optimization. Of the several types of delay, this paper focuses on information delay, which depends on the flow of intangible assets. Firstly, determining the minimum delay in a SC is determined by linear programming is described. Then, SC performance is optimized by a genetic algorithm based on minimum of delay. Finally, a dynamic model of the interaction between delay and performance is developed. A case study is presented where this model was simulated and validated at the Alupan Company.

Keywords: Supply Chain Management (SCM), Performance, Information delay, Genetic Algorithm.

1 Introduction Supply chain management (SCM) is a major component of competitive strategy, with direct implications on organizational productivity and profitability (Afrazeh and Zarinozv, 2010; Beamon, 1999). Why some firms outperform others has long been a central question within the organizational literature (Bowersox et al., 2000; Afrazeh and Bartsch, 2007). Recent years have seen an acceleration of interest in the analysis, management, and control of supply chains (SCs). The success of any SCM system depends on its developer's and adopter's capabilities. These include capabilities in developing a flexible organization, building strong relationships with suppliers Achieving these capabilities requires innovative personnel Such a team will reduce delays in project implementation with their fast and appropriate decision making, and this will lead to optimization of the production chain. Companies define the effectiveness of SCM activities in terms of the emphasis placed on developing human resources and re-training of staff (Bowersox et al., 2000). This includes development in the following four skill areas: problem solving, leadership, group making, and job-related skill. All four skills determine staff capabilities and 250


their development leads to a faster and more flexible SC with fewer delays. In addition, an effective SCM activity relies on team work and constant improvement, which can also reduce delays. We know little about the intangible aspects of why some SCs excel while others struggle (Wernerfelt, 2005), although much attention is focused on understanding performance differences between firms. Given the role of a SC in attaining core competency, it is necessary to study the factors that determine SC performance. In current competitive environment, time is one such critical factor: corporations that can quickly respond to environmental changes have a higher probability of success. In the literature of SC, we confront many issues. One of them is buffer management. In a SC, two types of transformations occur: physical transformation and information transformation. These transformations apply to both tangible and intangible assets, respectively. Consequently, we can also divide the buffer into two categories: intangible buffer and tangible buffer. Many researchers have studied the tangible buffer and the transformation of tangible assets in a SC. However, in this paper, the intangible buffer and scrutinize its effect on the productivity of a SC is addressed. Followed by a proposing a method for improving this productivity. To this end, the effects of delay on the intangible buffer and propose a method for optimizing this delay has been studied. Speed being a key determiner of competitiveness and organizational survival, we seek methods to optimize the response time through optimizing delay. The delay discussed in this paper is information delay. The delay divides into two categories: information delay and material delay. Here we propose a method for optimizing this delay and consequently improving SC performance. In this manner, optimizing the response time of a firm and improve their competitiveness would be possible. An enterprise must monitor how well it, its partners, and the entire SC are fairing, since “you cannot manage what you cannot measure” (Hult and Ketchen and Slater, 2004). That is, to improve SC performance, one must first measure that performance. Therefore, we first present existing models for SC performance measurement. After selecting a suitable model, the effect of delay on SC performance must be securitized.

2 Supply Chain Performance Management SCM is a technique developed for pure production systems and is also related to such systems (Bechtel, Jayaram, 2004). For most organizations, developing a pure production system is a key element of SC activities and consists of searching for cases such as improving the delivery value to customers, increasing the reliance on on-time production systems, eliminating wastage, increasing the stakeholders' focus on process value, developing close collaboration with suppliers, reducing the number of suppliers, and increasing suppliers' efficiency (Mabert and Venkataramanan, 1998). Brewer and Speh (2000) recommend the use of the balanced scorecard (BSC) as a framework for SC performance measurement. A BSC provides a struc251


ture to measure organizational performance from four perspectives: financial, customer, business process, and learning and growth. Metrics are developed for each of these perspectives and are combined to measure the SC performance. Chunhua et al. (2003) utilized this idea to develop the time, quality, cost, and flexibility (TQCF) model for measuring SC performance. They stated that C-type measures reflect the performance of the financial perspective, Q-type measures reflect the customer perspective, and the T- and F-types reflect the performance of the business process. However, due to its fuzziness, the learning and growth perspective is not reflected in this performance system. Chunhua et al. (2003) stated that the four perspectives, TQCF, reflect different properties of an entity. From the time dimension, C reflects past performance, T and Q reflect current performance, while F reflects the adaptability to future change. The interactions between the elements of the model are shown in Fig. 1: T

C Q

F

Fig. 1: Interaction between the elements of SC performance

There is a relationship network among the four parameters in which all affect each other. Thus, it is necessary to discover the relationship among the parameters and determine each one's effectiveness. However, time, though in harmony with the other three, is more important. Delay, which is closely related to the time factor, is also an independent parameter by itself and a system as well. All these lead to the independent examination of delay. Hence, in this research, the parameter delay is added to the other four parameters in the model and implementation. This analysis is evident in Figure 2. T

Q

C

F

Fig. 2: Importance of time in model

2.1 Delay in Supply Chain Management The essence of delay subjectivity is time. Time is a basic parameter of SC performance measurement. Though it may be initially assumed that time is the only pa252


rameter interacting with delay, this is not absolutely correct and we should consider other parameters affecting SC performance. Nevertheless, we optimize delay in terms of time: the purpose of this section is to increase the SC speed, improve performance, and decrease the total delay. Consider the process presented below: P1

D1

P2

Dn

Pn+1

Fig. 3: Process framework in chain format

Figure 3 shows delay in a SC including n interrelated and independent projects. In this chain, the delay among the projects is a buffer. In general these kinds of delays are information delay types. In other words, the current buffer in projects is in direct relation with the delay of the information type. Buffer creates delay in information flow, the nature of delay is not bad but it should be optimized. Is it necessary for information transfer from P1 to P2 with minimum delay. For example, suppose an operator must assess an instruction after completing P1, a suitable motion path according to the type of letter, and finally put it in the correct path. Is the delay created by the operator in the transfer process undesirable? No, delay is not absolutely undesirable because all of the activities performed by operators need minimum delay; therefore, the optimized delay may not be zero. For determining the optimized delay (Di*), we should first define other factors affecting Di and analyse the dynamics among these factors. The buffer includes three elements (ok, watch & plan, act), and delay has the same three elements (ok, watch & plan, act). These three elements are defined as follows: Ok: Necessary time for an activity acceptance; Watch & plan: necessary time for order understanding and planning of activity; Act: necessary time for plan implementation. Di could be optimized in two ways: first, assume that Di is independent of its system and optimize it according to itself. Thus, we must analyse the Di elements and interactions that may exist among them. Second, Di can be optimized as part of a system and the focus is optimization of the total system. As mentioned earlier, Di is calculated with formula 1: Di= Doi + Dwpi + Dai

Formula 1

The three types of delays mentioned above are as follows: Doi is needed when a person receives and confirms a reference topic. Dwpi is required when a person watches and plans for the reference topic. And Dai is used when a person acts on the reference topic.

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Doi: delay of ok in iteration i ; Dwpi delay of watch & plan in iteration i; Dai: delay of act in iteration i . At first, it is assumed that Dj is a function of one variable—this variable is time. Then, we add other variables to this function to make it more acceptable. We then try to optimize Dj as shown in Formula 2. MODEL: min = Doi + Dwpi +Dai; Doi

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