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A methodology for the reconfiguration process in manufacturing systems Ibrahim H. Garbie Department of Mechanical and Industrial Engineering, Sultan Qaboos University, Muscat, Oman and Department of Mechanical Engineering at Helwan, Helwan University, Cairo, Egypt

A methodology for the reconfiguration process 891 Received 22 June 2011 Revised 29 November 2011 20 February 2012 25 February 2012 30 April 2013 Accepted 30 April 2013

Abstract Purpose – The purpose of this paper is to propose a “Reconfiguration Methodology” in manufacturing systems that they can become more economically sustainable and can operate efficiency and effectively. This methodology will allow customized flexibility and capacity not only in producing a variety of products (parts) and with changing market demands, but also in changing and reengineering the system itself. Design/methodology/approach – Reconfigurable manufacturing system (RMS) is a philosophy or strategy which was introduced during the last decade to achieve agility in manufacturing systems. Until now, the RMS philosophy was based changing activities such routing, planning, programming of machines, controlling, scheduling, and physical layout or materials handling system. But the RMS concept can be based on the needed reconfiguration level (NRL), operational status of production systems, and new circumstances (NC). The NRL measure is based on the agility level of the manufacturing systems which is based on technology, people, management, and manufacturing strategies. The components of the manufacturing system design (MSD) consist of production system design, plant layout system, and material handling system. Operational status of production systems includes machine capability (flexibility) and capacity (reliability), production volume or demand, and material handling equipment in addition to the plant layout. The NC are also consisting of new product, developing the existing ones, and changing in demand. Findings – Reconfiguration manufacturing systems from one period to another period is highly desired and is considered as a novel manufacturing philosophy and/or strategy toward creating new sustainable manufacturing systems. A new reconfiguration methodology for the manufacturing systems will be analyzed and proposed. Two Case studies will be introduced. Originality/value – The suggestion of a new methodology of reconfiguration including the NRL (configurability index) and the operational status of manufacturing systems with respect to any circumstance is highly considered. The reconfiguration methodology also provides a framework for sustainability in the manufacturing area which mainly focussed on manufacturing systems design. Keywords Reconfigurable manufacturing systems, Manufacturing strategies Paper type Research paper

1. Introduction A reconfigurable manufacturing system (RMS) is considered to be a new philosophy of manufacturing. The RMS is designed for rapid adjustment to customized production capacity and functionality, in response to new circumstances (such as, introducing a new product and/or changes in market demand), and is done by rearrangement of or changing of its components (Koren et al., 1999; Koren, 2010). Because the RMS is defined for rapid adjustment, it can be considered to be a new strategy or philosophy for manufacturing systems that will allow flexibility not only in producing a variety of products (parts) and changing market demands, but also

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in changing the system itself. Reconfiguration of manufacturing systems may require changing different types of activities such as routing, scheduling, planning, programming of machines (e.g. CNC), controlling, physical layout by adding and removing machines and their components, material handling systems, and/or configuration of machines into workstations (cells) (Youssef and EL Maraghy, 2006a). Because agility is still used to update the level of manufacturing firms for competition or industry modernization programs, the philosophy of RMSs appeared as one of the manufacturing strategies to achieve agility in manufacturing systems. While agility means different things to different enterprises under different contexts, the following elements capture its essential concept (Koren et al., 1999). Agility is characterized by cooperativeness and synergism, a strategic vision, responsive creation and delivery of customer-valued services, nimble organization structures, and an information infrastructure. Because the evaluation of manufacturing firms for a needed reconfiguration level at any time will be a very important issue, the needed reconfiguration methodology level at any time also depends on the current agility level and the status of manufacturing systems design (Garbie, 2008a, b). This paper focusses on the analysis and methodology of manufacturing systems for a reconfiguration level at any time based on the needed reconfiguration level (Garbie, 2008a, b) and the status of manufacturing system design. Because the important aspect of any manufacturing system is the design of its system, integrating the material handling system (MHS ) and plant layout system (PLS ) is a very highly important issue. Therefore, status of the manufacturing system can be divided into three main parts: production system, material handling system, and plant layout system. In reconfiguration, the manufacturing system will reuse and reconfigure manufacturing components of the original system in the new configuration. These components are the number of machines in the system (processing resources and material handling equipments) and the configuration of the plant (plant layout). All components have significant effects on reconfiguration. The production systems with multiple stations are called a flow shop (e.g. assembly line, transfer line, production line), functional (process) shop, or cellular system depending on its configuration, size, and function. The size and functionality of each production system will be different based on the number of machines or workstations in the production system, number of shifts, number of hours per shift, and part or product variety (Groover, 2009). Although the material handling system (MHS) cost can comprise between 30 and 70 percent of the total manufacturing cost (Sule 1988) and it is considered by many to be the backbone of manufacturing systems, studying only the material handling system (MHS ) with respect to reconfiguration is not enough. Also, the MHS in any production system plays an important role in the performance of the entire manufacturing system although it was considered as non-productive equipment (means non-value added). Regarding the configuration, the type of plant layout has a very significant impact on the structure and operation of a production system (Abdul-Hamid et al., 1999). Therefore, the layout defines the basic structure of the manufacturing system and has a very significant impact on the organization, operation, and technical and human issues in the plant (Black, 1991). This paper is organized into several sections. Section 1 presents the importance of reconfiguration and agility in manufacturing systems. Section 2 reviews the previous research about the reconfiguration and its issues regarding the manufacturing systems. Analysis of manufacturing firms regarding the reconfiguration process is presented in Section 3. Section 4 introduces the proposed reconfiguration process.

The Case studies will be introduced in the Section 5. Finally, the discussion, conclusions, and recommendations for future work are given in Section 6. 2. Related review 2.1 Literature review related to the reconfiguration strategy Abdi and Labib (2003) suggested a design strategy for RMSs by comparing the RMS with conventional manufacturing systems (e.g. cellular manufacturing system (CMS) and flexible manufacturing system (FMS)) and traditional manufacturing systems (e.g. dedicated manufacturing system (DMS)). Their strategy was explained by analyzing traditional manufacturing systems with their competitive criteria and objectives. Selection of the preferred manufacturing systems was validated by using the Analytical Hierarchy Process (AHP). Abdi and Labib (2004b) proposed a model for insight into a feasibility study for an RMS design by considering the importance of manufacturing capacity and functionality. Lee (1997) presented a reconfiguration of a flow line manufacturing system based on the relationship between part routes, material handling costs, and reconfiguration costs. The new requirements for RMSs were introduced and discussed by several researchers along with their key role in future manufacturing (Koren et al., 1999; Mehrabi et al., 2000). They deal with the RMS as a general framework with a historical review of a manufacturing system. Reconfigurable machines were introduced into the RMS as a key research issue for the Next Generation Manufacturing Systems (NGMS) to survive in the new competitive environments through the year 2020 (Molina et al., 2005). In the NGMS, the structural design of reconfigurable machines, open machine tool controllers, simulation, and process-oriented programming systems were included. A scalable machine was proposed as meeting the need for scalability for reconfiguration through a modular architecture (Spicer et al., 2005). Singh et al. (2007) used a decision-making module to evaluate existing and new generation manufacturing systems by trading off among tangible and intangible design parameters. Matta et al. (2008) proposed optimal reconfiguration policy to react to product changes based on uniformly distributed market demand and technological requirements. Liu and Liang (2008) focussed on reconfigurable machine tools (RMT) taking into consideration three important conflicting factors: configurability, cost and process accuracy. Zhang and Rodrigues (2009) proposed Petri net (PN) techniques to model RMSs with focus on the process of reconfiguring system elements while considering constraints and system performance. Dou et al. (2010) presented a genetic algorithm (GA) for optimizing (minimizing) capital cost of multi-part flow line (MPFL) configurations of RMS for a part family. Garbie (2013a) suggested a conceptual framework for a design for reconfiguration taken into consideration globalization issues and aspects. Garbie (2013b, 2014) presented RMSs as one of most important aspects of economic sustainability in manufacturing enterprises. 2.2 Literature review related to the production system design Saad (2003) suggested and presented the CMS as a reconfiguration design issue. His work concentrated on a reconfigurable manufacturing cell based on grouping parts (products) into part (product) families. Galan et al. (2007) presented a new methodology for grouping products into families which was considered to be the main issue in the design of a RMS. It considered five key requirements of products to be grouped in an RMS. These keys are: modularity, commonality, compatibility, product reusability, and product demand. Abdi and Labib (2004a) proposed a methodology for classifying,

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selecting, and grouping products into product families using the AHP in manufacturing and assembly systems. Tang and Qiu (2004) introduced an algorithm for balancing the flow line production system to maximize the productivity and utilization of the RMS. Altemeier et al. (2010) presented a mathematical optimization model to minimizing the costs of auto production under the influence of a huge product variety. Ahkioon et al. (2009) provided in-depth discussions on the trade-off between increased flexibility obtained through routing flexibility vs additional cost due to machines procurement in CMS. 2.3 Literature review related to the material handling and plant layout Wong et al. (2007) explained how online reconfiguration can help to enhance the operational and recovery routing flexibilities of automated material handling equipment. Orday et al. (1995) developed an algorithm to help in making decisions in the selection of alternative designs of a MHS for agile manufacturing cells. Ioannou (2007) presented an integrated shop design model to incorporate resource groups on the shop floor with the transporters (equipment) and routing flow. Meng et al. (2004) introduced a layout system as a reconfigurable layout problem assuming that the production data are available only for the current and upcoming production period. They recommended a cellular layout as the reconfigurable layout. The main issues of selecting a suitable type of layout for components of a manufacturing plant were analyzed using the AHP (Abdul-Hamid et al., 1999). Group technology (cellular layout) was ranked as the highest score in satisfying the suggested attributes and the best one to be applied in the plant. Khan and Gwee (1997) introduced production flow analysis (PFA) as a cell formation technique to convert the functional (process) layout of the factory into a cellular layout to apply the just-in-time ( JIT) principle. Youssef and El Maraghy (2008) used GAs and tabu search for optimizing capital cost and system availability of the RMS configurations based on arrangement of machines, equipment selection, and assignment of operations. 2.4 Literature review related to the analysis and measurements The level of reconfiguration smoothness (RS) was developed to provide a relative measure of the expected cost, time, and effort required to convert from one configuration to another system-level configuration (Youssef and El Maraghy, 2006a). A model for optimizing the capital cost with several types of parameters and constraints was presented using a GA (Youssef and El Maraghy, 2006b). Garbie et al. (2008b) presented a new measurement methodology of a needed reconfiguration level for manufacturing firms based on the current agility level and status of the manufacturing system design. Gumasta et al. (2011) developed an index to measure the reconfigurability of RMSs keeping in mind their various core characteristics such as: modularity, scalability, convertibility, and diagnosability. 2.5 Summary of the literature review The following comments are related to this review of the literature: .

Most of the research in this field has been in the area of analysis rather measurement without taking into consideration the main issues of reconfiguration together.

.

CMSs design (layout) is the most recommended manufacturing system design and configuration type for the RMS.

.

Until now, very little work dealing with the reconfiguration strategy in detail for the RMS has been published.

.

There is a major shortcoming in most of the research done by neglecting the effect of the agility level on the level of reconfiguration (Garbie et al., 2008b).

.

The reconfiguration methodology evaluation level is not presented after the reconfiguration period.

For these reasons, analysis of reconfiguration issues and a new methodology for the reconfiguration of manufacturing firms still needs more attention. The contribution of this paper is a framework to present a reconfiguration methodology which includes three phases: production system phase, plant layout system phase, and material handling system phase. This will depend on the need for manufacturing firms to reconfigure considering the needed agility level and framework status of the manufacturing system design. 3. Analysis of reconfiguration processes Because the manufacturing systems should be managed to respond quickly and cost effectively, these systems should be discussed and analyzed to improve their performance. In this paper, analysis for reconfiguration processes is suggested to answer three important questions “When do we reconfigure manufacturing firms?” “How do we reconfigure manufacturing firms?” and “How do we evaluate reconfiguration processes?” The first two questions were only verbally suggested by Saad (2003) in order to design a CMS as a primary requirement and reconfiguration as a secondary requirement. In this paper, answers to the first and second questions will be introduced, but the explanation of the third question will be discussed and presented in the next research work. 3.1 When do we reconfigure the manufacturing firm? Analysis of reconfiguration processes will depend on the needed reconfiguration level at any time t noted as NRL(t), reconfiguration methodology level RML(t), and performance measurement level PML(t) (see Figure 1). The NRL(t) was measured based on the needed current agility level (NAL), the status of manufacturing systems design (MSD), and the new circumstances. The NRL(t) is clearly expressed as shown in the following equations: NRL(t) ¼ f (Needed Current Agility Level, Status of Manufacturing Systems Design, New Circumstances): NRL ðtÞ ¼ f ½NALðtÞ; MSDðtÞ; NCðtÞ

ð1Þ

NRL ðtÞ ¼ w1 ½NALðtÞ þ w2 ½MSDðtÞ þ w3 ½NCðtÞ

ð2Þ

where w1, w2, and w3 are the relative weights of the needed agility level, status of the manufacturing systems design, and new circumstances, respectively. The needed agility level NAL(t) is clearly expressed as the following equations: NAL ðtÞ ¼ wTE ð1 ATE Þ þ wPE ð1 APE Þ þ wMA ð1 AMA Þ þ wM ð1 AM Þ

ð3Þ

Equation (3) can be rewritten with different nomenclature: NAL ðtÞ ¼ wTE ðNALTE Þ þ wPE ðNALPE Þ þ wMA ðNALMA Þ þ wM ðNALM Þ

ð4Þ


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New Product, NP

Technology, TE

896 People, PE

Demand Changes, DC Product Development, PD

New Circumstances, NC (t )

Needed Agility Level, NAL (t )

Status of Manufacturing System Design, MSD (t )

Manufacturing Strategies, M Management, MA

Needed Reconfiguration Level, NRL (t )

Material Handling System, MHS Plant Layout System, PLS

Production System Size and Functionality, PSS & F

Reconfiguration Methodology, RML (t )

Phase I: NRL (t) Evaluation Phase II: ProductionSystem (PS ) Phase III: Plant Layout System (PLS ) Phase IV: Material Handling System (MHS )

Figure 1. A framework of reconfiguration process

Performance Measurement Level, PML (t )

where ATE is the agility of technology infrastructure, NALTE the needed agility level of technology infrastructure ¼ 1ATE, APE the agility of people infrastructure, NALPE the needed agility level of people infrastructure ¼ 1APE, AMA the agility of management infrastructure, NALMA the needed agility level of management infrastructure ¼ 1AMA, AM the agility of manufacturing strategies infrastructure, NALM the needed agility level of manufacturing strategies infrastructure ¼ 1AM. The symbols wTE, wPE, wMA, and wM are the relative weights of technology, people, management, and manufacturing strategies, respectively. The value of these weights may reflect the system designer’s subjective preferences based on his/her experience or

can be estimated using tools such as AHP (Garbie, 2012). In this paper, the relative weights of criteria using the AHP are estimated and changed frequently according to new circumstances specified by the decision maker or groups of decision makers. These groups represent manufacturing engineers, plant managers, operators, and suppliers. Pair-wise comparisons of the criteria are used for a particular manufacturing system design and performance analysis (Garbie, 2013b, 2014). With the status of manufacturing system design (MSD), it was divided into three main parts. The first part is the production system size and functionality (PSS&F). The second part is the plant layout system (PLS). The last part is the material handling system (MHS). The general equation to measure the MSD will be shown in the following: MSD ðtÞ ¼ wPSS&F ðAttributesSSS;MSS;LSS;RC;RF;RU ;PPL;MS&W Þ þ wPLS ðAttributesCL;PL;FL Þ þ wMHS ðAttributesMHE;MHSS;IS Þ

ð5Þ

where wPSS&F is the relative weight of production system size and functionality, wPLS the relative weight of plant layout system, WMHS the relative weight of material handling system, SSS the small-sized manufacturing system, MSS the medium-sized manufacturing system, LSS the large-sized manufacturing system, RC the resource capacity, RF the resource capability or flexibility, RU the resource utilization, PPL the physical product limitations, MS&W the machine size and weight, PLS the plant layout system, CL the cellular layout, PL the product layout, FL the functional or process layout, MHE the material handling equipment, MHSS the material handling storage system, and IS the identification system. The symbols wPSS&F, wPLS, and wMHS are the relative weights of production system size and functionality, plant layout system, and material handling system, respectively. The relative weights of criteria are also estimated and changed frequently according to the new circumstances using the AHP. With respect to the new circumstance NC(t), it is also clearly expressed as the following equations: NCðtÞ ¼ f ½NPðtÞ; PDðtÞ; DCðtÞ

ð6Þ

NC ðtÞ ¼ wNP ½NPðtÞ þ wPD ½PDðtÞ þ wDC ½DCðtÞ

ð7Þ

where NP(t) is the attribute value of a new product, PD(t) the attribute value of a product development, and DC(t) the attribute value of changing demand. The symbols wNP , wPD , and wDC are the relative weights of introducing a new product(s), product development, and changing in market demand, respectively. The relative weights of criteria using the AHP are estimated and changed frequently according to new circumstances specified by the decision maker or groups of decision makers. Therefore, the needed reconfiguration level at any time NRL(t) can be represented by Equations (8) or (9) as a function of all items (issues) in a manufacturing system (business and manufacturing issues): NRL ðtÞ ¼ f ðTE; PE; MA; M ; PSS F; PLS; MHS; NP; PD; DCÞ

ð8Þ


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where TE is the technology infrastructure, PE the people infrastructure, MA the management infrastructure, M ¼ manufacturing strategies infrastructure, PSS&F the production system size and functionality, PLS the plant layout system, MHS the material handling system, NP the new product, PD the product development, and DC the demand change.

898

4. A methodology for the reconfiguration process A methodology for the reconfiguration process is used to answer the second question which was stated under titled “How we do reconfigure manufacturing systems.” The reconfiguration process consists of four phases: NRL(t) (configurability index (CI )), production system analysis, plant layout system analysis, and material handling system analysis. Identifying the NRL needed reconfiguration level NRT(t) measure for each manufacturing system is highly valuable. The NRL(t) evaluation has a certain level of needed reconfiguration. It was based on the agility of the manufacturing firms and current status of the manufacturing systems design for these firms. Production system analysis was based on small-sized systems, machine capacity and capability (flexibility), machine utilization, product physical limitations, and machine weight and size. Also, plant layout system analysis was based on cellular layout with a U-shape. Finally, material handling system analysis was mainly based on material handling equipments. Based on these analyses, the reconfiguration process is identified as follows: Phase I: evaluate the needed reconfiguration level (configurability index) Check the NRL (t) If the NRL(t) is 450 percent (authors judgment), there is a need to reconfigure the manufacturing system according to the relative weights of agility and status of the manufacturing system, otherwise stop. Phase II: production system Step 1: estimate the new circumstance: changing demand (DC ) for the existing product(s) (increasing or decreasing), changing the product development (PD), and introducing a new product (NP) in the next period. k ¼ 1, 2, y, K where k ¼ subscript of products). Step 2: check the existing production system size and type. If there is a small-sized production system with a cellular system and/or flow line systems. If there is a medium-sized production system and/or large-sized production system in job shop environment (functional or process), divide them into a small-sized with cellular system and/or flow line system. Step 3: estimate the production rate PRk(t) of product k based on the changes in demand over time from period to period, changes in the product development, and/or introduction of a new product based on a cellular production system or flow line systems: n ðtÞ

PRK ðtÞ ¼

ok 1 X 1 nok ðtÞ i¼1 Tcki ðtÞ

ð9Þ

where nok(t) is the number of machines required to process product k at time t. Tcki ðtÞ ¼ production time per product k on machine or operation i at time t: Tcki ðtÞ ¼ tnoki ðtÞ þ tmki ðtÞ þ ttctki ðtÞ

ð10Þ

where tnoki ðtÞ ¼ non-production time or a setup time for product k on machine or operation i at time t, tmki ðtÞ ¼ machining time for product k on machine or operation i at time t, ttctki ðtÞ ¼ tool changing time for product k on machine or operation i at time t. Step 4: estimate the resource work load (RWLi(t)) of all existing machines at time t. The RWL of resource i in the plant or factory at time t must be determined as follows: RWLi ðtÞ ¼

K X

Dk ðtÞ Tcki ðtÞ

ð11Þ

k¼1

Dk(t) represents the demand or production volume of product k at time t. Step 5: estimate the resource capacity (reliability), Rci(t) of all existing machines. Step 6: check the resource capacity: .

If there is enough capacity, go to the next step.

.

Otherwise, more capacity is needed. Capacity may be increased as follows: add more working hours (overtime), increase the number of shifts, or add new machines.

.

If there is excess capacity, reducing the number of working hours, decreasing the number of shifts, or removing some machines may be desirable.

Step 7: calculate the resource utilization. Resource i utilization RCi(t) in the factory or plant at time t will be evaluated as follows: RWLi ðtÞ ¼ RUi ðtÞ ¼ RCi ðtÞ

PK

k¼1

Dk ðtÞTcki ðtÞ RCi ðtÞ

ð12Þ

where RCi(t) ¼ capacity of resource i at time t. Step 8: check each resource utilization: .

If the resource utilization is high, go to the next step.

.

Otherwise, if the resource utilization is low, relocation of a machine or operation is required.

Step 9: calculate the plant or system utilization The plant or system utilization (SU) refers to the actual amount of output of a production facility relative to its theoretical capacity. It can be formulated as follows: n ðtÞ

SU ðtÞ ¼

o 1 X RUi ðtÞ no ðtÞ i¼1

ð13Þ

where no(t) ¼ number of machines available in the plant. Step 10: estimate the production volume flexibility. Existing production volume flexibility (PVF) should be related to the slack capacity in the system. Hence, PVF (t) is directly measured related to the slack capacity built


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into the system. This measure ranges from 0 to 1. This attribute can be defined by the following equation: n ðtÞ

PVFðtÞ ¼

900

i 1 X SRCi ðtÞ ni ðtÞ i¼1 RCi ðtÞ

ð14Þ

where SRCi(t) ¼ slack in resource capacity i at time t: SRCi ðtÞ ¼ RCi ðtÞ RWLi ðtÞ RCi(t) is the capacity of resource i at time t, and RWLi(t) is the resource work load i at time t. Step 11: estimate the resource capability (flexibility) in all existing resources. The resource capability (flexibility) RFi can be estimated by the number of operations a machine can perform relative to those required by a given set of part types, by how well it can perform them, and by how well it can switch operations. The resource capability can be proposed to be used as follows when it can be used at the first time: RFi ðtÞ ¼

noi ðtÞ Noimax ðtÞ

ð15Þ

where RFi(t) is the resource flexibility or capability i at time t, noi ðtÞ ¼ number of operations that can be done on resource i at time t, Noimax ðtÞ ¼ maximum number of operations available on resource i at time t, 0 ¼ subscript of operations, 0 ¼ 1, 2, y, 0. The resource capability inside the plant after processing K products will be assessed by the resource processing capability and capacity rather than with Equation (17). This capability will be used to measure the machine that has an automatic tool changer or tool magazines to perform the new operations. It can be expressed by Equation (18) as shown below. This equation is used when accepting a new product:

RFi ðtÞ ¼

oi ðtÞ K nX X SRCi ðtÞ SRFi ðtÞ k¼1 o¼1

RCi ðtÞ

Noimax ðtÞ

ð16Þ

where RFi(t) is the resource flexibility or capability i at time t, SRCi(t) the slack in resource capacity i at time t. SRCi ðtÞ ¼ RCi ðtÞ RWLi ðtÞ SRFi(t) is the slack in resource flexibility or capability i at time t. SRFi ðtÞ ¼ Noimax ðtÞ noi ðtÞ Step 12: check for machine flexibility or capability. If there is enough capability, go to the next step. Otherwise, more capability is needed. Capability may be increased as follows: add new tools or tool magazines or add new machines (e.g. CNC).

Step 13: estimate the product (product-mix) flexibility. New product flexibility (PFk(t)) will be assessed by the capability of all manufacturing facilities which are needed in the plant. Product flexibility can be used to evaluate the ability of a plant to accept a new product. It can be expressed as follows:

A methodology for the reconfiguration process

n ðtÞ no ðtÞ

i i X 1 X SRCi ðtÞ SRFi ðtÞ PFk ðtÞ ¼ ni ðtÞ i¼1 o¼1 RCi ðtÞ Noimax ðtÞ

ð17Þ

where ni(t) is the number of machines that can be used to produce product k at time t. Step 14: check the new product flexibility value. If the flexibility is greater that 0, go to the next step. Otherwise, go back to Steps 6 through 11. Step 15: stop. Phase III: Plant layout system (PLS) Step 16: classify the types of manufacturing system layouts (configuration). Step 17: check the type of each layout. If there are cellular layouts and/or product layouts, they will be easy to reconfigure. Otherwise configurations such as fixed layouts and/or functional (process) layouts are very difficult to reconfigure. If they exist, go back to Step 2 to convert the functional or process layout into cellular layout and/or flow line layout. Step 18: check for space limitations. The space limitations include the length and width of the area available for the configuration or reconfiguration: .

The length can be translated into the maximum number of workstations (stages).

.

The width can be translated into the maximum number of parallel machines or stations within a stage.

.

If the number of workstations needed is less than the maximum number available, go to the next step. Otherwise, more space is needed.

Step 19: check the operations sequence of the material handling equipment (it should be bidirectional). Step 20: check the number of locations available for machines. Step 21: check for lowest relocation cost (it should be a minimum cost). Step 22: check the machine size and weight. Step 23: check the physical product limitations. Step 24: stop. Phase IV: material handling systems (MHS ) Step 25: classify the types of material handling systems. Step 26: rank the equipment according to its position regarding the reconfiguration. Weight 9 for vehicles and trucks, weight 3 for conveyors, and weight 1 for hoists and cranes are used to evaluate the material handling equipment. Step 27: check the material handling equipment. If there are vehicles and trucks to reconfigure. Go to next step. Otherwise, the material handling equipment will be difficult to reconfigure, they will be easy.

901

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Step 28: estimate the material handling system capacity and flexibility according to the fluctuation of demand based on Equation (18) (Beamon, 1998):

MHFk ðtÞ ¼

ni ðtÞ X

xi ðtÞmi ðtÞui ðtÞei ðtÞbi ðtÞ

ð18Þ

i¼1

902 where MHFk(t) is the material handling equipment flexibility and capacity, x i(i ) the number of material handling equipments of type i at time t, mi(t) the maximum unit load quantity factor based on the capacity of the equipment at time t, ui(t) the equipment speed based on the normal operating speed of the equipment at time t, ei(t) the equipment loaded travel factor at time t, bi(t) the relative rerouting cost indicating ability of the equipment to reconfigure at time t, and ni(t) the total number of material handling equipments used at time t. Step 29: check the material handling equipment capacity and flexibility. If sufficient capacity and flexibility are available, go to the next step. Otherwise, more capacity and flexibility can be obtained by adding new equipment or by replacing the existing equipment with new equipment. Step 30: stop. All these steps are shown in the following Figure 2. 5. Case studies and analysis 5.1 Case study No. 1 (XYZ Company) XYZ Company is the only extrusion company in the Sultanate of Oman. The company has a unique process of powder coating applications for the manufacture of aluminum products and accessories. More than 80 percent of its products are used by the construction and architectural sectors for doors and windows. The product range includes mill finished products, powder spray painting, anodizing and wood coated products. Online monitoring, offline quality checks, and preventive maintenance practices are applied to achieve precision and a high level of quality. The company has International Organization of Standardization (ISO) certification (e.g. 9000-9001) that ensures premium quality of their products. Almost 80 percent of their material is derived from raw materials while the remaining 20 percent is scrap sent back to the original supplier. The company is a major exporter, exporting 60 percent of its product to Gulf countries, 12 percent to Europe, and almost 20 percent to other neighboring countries like India, Pakistan and Africa while the remaining 8 percent remains in Oman. 5.1.1 Analysis of existing factory. (1) Production system analysis. The production plant is operating at full capacity in three shifts (24 hours per day) and has the capacity to produce over 180,000 tonnes per annum of high yield strength aluminum bars in different sizes. The plant is equipped with two highly automated extrusion machines on two production lines based on German and Italian technologies. The first production line was installed in 1985 while the second was installed later, in 2003. The company purchases aluminum billets from a major supplier in Dubai, UAE. The material is heated in a furnace from 400 to 5201C and then cut into pieces to get the required shape and dimensions according to the specification of customers. The hot finished bars are subjected to an online heat treatment process to improve mechanical properties.


Start

903

Measure the NRL (t)

No, if NRL (t) is less than 50% Is there a need to reconfigure?

Stop

Yes, if NRL (t) is greater than 50% Estimate the new circumstances (NC)

Introducing new product (NP)

Large-sized production system

Changing demand (DC)

Changing product development (PD)

No

Divide the large-sized production system into a small-sized or medium sized production system with a cellular system and/or flow line system

Check the existing production system size and type.

Yes

Medium-sized production system with a cellular system and/or flow line systems

Yes

Small-sized production system with a cellular system and/or flow line system

Estimate the production rate

Estimate the RWL (t) of all existing machines

A

(continued)

Figure 2. Flow chart of reconfiguration process

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904

Estimate the resource capacity (reliability) of all existing machines

Add more working hours (Over time)

Reducing # of working hours No Decrease number Of Shifts

No Is thre enough capacity?

Excess capacity

Removing some machines

Increase number of shifts

More capacity is needed

Adding new machines

Yes

Machine utilization Manufacturing Firm Utilization

Check the machine flexibility (capability) in all existing machines and/or new machines

Add new tools

No Is there enough capability?

More capability is needed

Added new machines

C

Yes Estimate the product flexibility

Is product flexibility value>0?

No

Yes B

Figure 2.

(continued)


B

Classify the types of manufacturing system layout

905 Rank the configuration types No No Convert process layout to cellular layout and/or flow line layout

Check the type of each layout

Functional (process) layout

Stop

Fixed layout

Yes

Cellular layout and/or flow line layout

Check for space limitations

Check operations sequence

Check Machine size and weight

Check number of locations available for machines

Check the lowest relocation cost

Classify the types of materials handling systems Rank the equipment type

No Stop

Hoists and cranes

Check the type of material handling equipment.

No Conveyors

Stop

Yes

Vehicles and trucks Estimate the material handling system capacity and flexibility

Is the capacity and flexibility available?

More capacity (equipment) and flexibility are needed

Add new equipment

Replace existing equipment

Yes Stop

Figure 2.

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(2) Plant layout. The plant consists of two similar production lines (flow shop systems). This plant has a product-oriented layout with mixed product models. This layout is shown in Figure 3. (3) Material handling system. The material handling system in the plant is varied. There are many conveyors, including overhead conveyors, industrial vehicles, hoists and cranes. There is also a hand crane to transport finished products from the workshop to final product storage. To accomplish design and specification needs of customers, the dies are kept in stock and can be retrieved easily through an automated computerized storage and retrieval system (AS/RS). Different colors and codes are also used for material identification purposes. This advanced material storage system facilitates the company in the production of a great variety of aluminum bars. Based on these analyses of the XYZ Company, the question regarding reconfiguration should be addressed both in regards to the reconfiguration process itself, as well as where the process can occur and which plans should be implemented. It is estimated that by 2015 an increase in demand for aluminum products 270,000 tonnes per annum as the Gulf region becomes increasingly central and globally important within for the industry. There has already been a 50 percent rate of increase in demand aluminum products (270,000180,000/180,000 ¼ 0.50). Therefore, it can be noted from this new circumstance that a change in market demand is already under way, and the plant does not have any way to meet this rapid increase in demand through use of its existing two production lines, even though they are working 24 hours per day. Also, there is no way to use an overtime strategy. The best way to overcome this obstacle of insufficient production is to construct another production line. The company has enough space to build this line after removing rocks from the proposed expansion area behind it (Figure 3). 5.1.2 Reconfiguration process of XYZ Company. The first step in reconfiguring the XYZ Company is to evaluate the needed reconfiguration level (NRL) (Equation (2)). Measurement of the agility level (AL) is divided into four main infrastructures: technology (TE), people (PE ), management (MA), and manufacturing strategies (M). The total plant AL was 0.53 (53 percent) and the TE, PE, MA, and M agility levels were estimated as 0.744, 0.588, 0.862, and 0.248, respectively. The needed agility level (NAL) is estimated using Equation (3) by calculating the relative weights between TE, PE, MA, and M as shown in the following matrix. As a result, the relative weights

Expansion Area AS/RS

Production Line #2 Packaging

Figure 3. The existing plant layout of the XYZ company

Raw Materials Storage

Production Line #1 Parking Lot

Administration

Shipping

Final Products Storage

are estimated using the AHP for agility elements as (0.13, 0.42, 0.23, and 0.22). Then, the NAL is estimated at 0.358: 2 3 1 0:5 0:33 0:50 62 1 3 2 7 7 AL ¼ 6 4 3 0:33 1 1 5 2 0:50 1 1


Regarding the status of the manufacturing system design (MSD), which is based on Equation (5), the relative weights of production system size and functionality (PSS&F ), plant layout system (PLS), and material handling system (MHS) are estimated from the following matrix. As a result, the relative weights are estimated for the MSD elements as (0.50, 0.25, and 0.25) for PSS&F, PLS, and MHS, respectively: 2 3 1 2 2 AMSD ¼ 4 0:5 1 2 5 0:5 1 1 For the attributes of the PSS&F, it can be suggested that the attributes values are presented according to Table I. These values represent how much effort is necessary to reconfigure each component in the manufacturing system. For example, the attribute of small-sized systems is represented by one. This means that no great effort is necessary to reconfigure it. For medium-sized systems, this value will range from 1 to 2, and so on. Therefore, attributes of PSS&F equal 0.4 (10.900.980.900.51). The attributes of PLS and MHS are shown in Table II, with feasible and recommended values.

Main element

Attribute

Production system size

Small-sized system, SSS Medium-sized system, MSS Large-sized system, LSS Resource capacity, RC Resource flexibility, RF Resource utilization, RU Physical product and limitations, PPL Small size, S Medium size, M Large size, L

Resource capacity (reliability) Product size and limitations Machine size and weight

Main element

Attribute

Plant layout system, PLS

Cellular layout, CL Product layout, PL Functional layout, FL Material handling equipment, MHE Material handling storage system, MHSS Identification system, IS

Material handling system, MHS

Range of value

Recommended value

0.1-1 1-2 3-6 0.1-1 0.1-1 0.1-1 0.1-1 0.5-1 1-2 3-6

n/a 1 n/a 0.90 0.98 0.90 0.50 n/a 1 n/a

Range of value

Recommended value

1 1 3-5 1-5 1-3 1-2

n/a 1 n/a 3 1 1

Table I. Attribute values of the MSD

Table II. attributes values of the PLS and MHS

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One attribute of the existing PL is the product-oriented layout. Therefore, the PLS equals one. Regarding the MHS, the MHE is divided into conveyors, industrial vehicles, monorails, hoists and cranes; the effort required to operate each ranges from 1 to 5: 1 for the least effort regarding the operation of industrial vehicles, 3 for conveyors and 5 for monorails, hoists, and cranes. Because the new production line will be identical to the one now installed, the types of MHEs will also remain consistent. The MHSS also ranges from 1 to 3 based on the need for change in volume of storage. It is recommended to be set at 1 because there is enough storage for existing and future expansion. Also, there is AS/RS to store in addition to retrieving dies. There are different colors and codes for material identification purposes. Therefore, there is no need for more identification systems. In this case, the attributes of PL equal one and the attributes of MHS equals 3 (3 1 1). Finally, the MSD as referred to in Equation (5) is estimated as follows: MSD ¼ 0:50ð0:40Þ þ 0:25ð1:0Þ þ 0:25ð3:0Þ ¼ 1:20 ¼ 120% With respect to the new circumstances (NC), the only change will be represented as a changing demand from 180,000 to 270,000 tonnes per annum. The percentage of change equals 50 percent (270,000180,000/180,000 ¼ 0.50). The attributes of a change in demand is estimated to be 1.50, and the attributes of new product and product development are similar and equal to one, respectively. The relative weights of NC will be estimated by using AHP and the following matrix: 2

ANC

1 ¼ 41 2

1 1 2

3 0:5 0:5 5 1

As a result, the relative weights are estimated for NC elements as (0.25, 0.25, and 0.50) for new products, product development, and changing demand, respectively. The value of NC is estimated using Equation (7) as follows: NC ¼ 0:25ð1:0Þ þ 0:25ð1:0Þ þ 0:25ð1:5Þ ¼ 1:50 ¼ 150% The NRL is calculated by using Equation (2) after estimating the relative weights between NAL, status of MSD, and NC. The following matrix to estimate the relative weights is presented as the following matrix and the values are estimated for NRL elements as (0.40, 0.40, and 0.20) for NRL, MSD, and NC, respectively. Then, the NRL is estimated at 0.87 through the following equation: NRL ¼ 0:40ð0:358Þ þ 0:40ð1:20Þ þ 0:20ð1:25Þ ¼ 0:87 2

ANRL

1 ¼4 1 0:5

1 1 0:50

3 2 25 1

Phase II: production system (PS ) Steps 1 and 2: the new state or circumstance which compels adding a line is an increasing demand for product-within the coming years Also, in regards to production

size and type, it is important to note that the existing plant’s two production lines working three shifts (24 hours per day) at the full capacity. Overtimes is not allowed and so a new production line must be added and operated at a full capacity to cover the demand requirements while keeping the same configuration of the old production lines. In this situation, the reconfiguration process will be done at the machines levels with the machines including changeable dies to meet the manufacturability requirements of each product. Therefore, there will be no changes to the configuration of existing production lines except for the change in adding the new line. This new line will use the same sequence and configuration as the lines currently in place. However, they will use a new version of the extrusion machine to increase the production rate to meet this increase in demand requirements. Phase III: plant layout system (PLS ) Steps 16 and 17: as the existing PL was a product-oriented layout (e.g. flow shop manufacturing system) and the needed production line will also be developed considering the necessities of an identical product layout. The new production line will be designed in the same fashion as the existing ones. Steps 18-23: the Company has space for the new expansion behind the existing production lines (Figure 4). The company is fortunate to have access to this land as this industrial estate’s pace for expansion is very limited because it is a mountain area. Phase IV: material handling systems (MHS ) Steps 25-27: because the new production line will have the same layout as the existing ones, the same MHS (equipment, storage, identification systems) are required. The AS/RS will be used for the new production line too. Steps 28-29: the new MHE (vehicles and overhead conveyors) will be added to the new production line with the ability to assist with production at full capacity, and with more than enough flexibility.


5.2 Case study No. 2 (ABC Company) The modern factory for chandelier art specializes in the design and manufacture of chandeliers. The ABC Company has been in business for more than 50 years. They produce high-quality, handmade chandeliers which decorate the Ancient Palace, Parliament, ministry buildings, many presidential palaces, and hotels in Egypt and as well as in buildings in the Arabian states. All the products are made from bronze and can be gold plated. The production of steel, classic and modern chandelier suites is according to the different tastes and budgets of the customers. Some of the products

Production Line #3 Packaging Raw materials storage

Production Line #2

AS/ RS

Production Line #1 Parking lot

Administration

Shipping

Final Products Storage

Figure 4. The new PL of the XYZ company

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that are produced by the factory include: Chand Amber, Lantern Barrile, Chand Lokenz, Chand Barre, and table marble. 5.2.1 Analysis of existing factory. (1) Production system analysis. The stages of production include sand casting, breaking up the mold, cutting, filling, drilling, grinding, metal turning, finishing area (inspecting and removing defects if found), polishing, painting, and final assembly. The factory produces two main products, chandeliers and wall candlesticks. The market demands for chandeliers and wall candlesticks are 110 and 75 units per month, respectively. The number of operations per product is approximately eight. The factory produces 50 models of chandeliers and 30 models of wall candlesticks. Each model consists of different numbers and types of parts. There is one shift per day (8 hours) and 25 working days per month. The non-operational time for all operations per finished product is added to the casting time of the product. (2) Plant layout. The factory consists of four multistory floors with a workshop area of 500 square meters. Although this factory is a multistory building, this type of layout is considered a functional or process layout. The ground floor of the factory is about 300 square meters. It includes a copper melting room, turning machines, cutting machines, an arc and electrical welding section, and a polishing section. The layout of the ground floor is shaped manufacturing cell with a U-shape. The ground floor is a workshop in which operations of deformation, hammering, assembly, and wiring and painting are performed. It also contains a small furnace for the production of complicated small shapes and contains raw material storage. The second floor contains some administrative offices for managers and customer services, and also storage for the finished products. The third floor contains some offices, but it still has a large empty space which is not being used. The fourth floor is used for finished goods. (3) Material handling. Material handling in the factory is done manually and will give more flexibility in reconfiguring production if any changes in the layout of the workshop are necessary. There is only one hand crane, which is used to transport finished products from the workshop on the ground to the fourth floor for storage. 5.2.2 Reconfiguration process of ABC company. The first step in reconfiguring this manufacturing firm is to measure the existing agility and the need for reconfiguration. Measuring the agility level is divided into four main infrastructures: TE, PE, MS, and M. The factory agility is 0.70 (70 percent), with this high value due to well-executed MS and M. TE needs to be modified. PE are highly skilled and not need additional training because they are artists. The NRL is 0.637 (63.7 percent) which is according to Garbie et al., 2008b higher than the minimum recommended value of 50 percent. This high NRL was due to the high factory agility level of this small-sized manufacturing (SSM) firm with its one copper melting furnace, two turning machines, and grinding machines. Replacing the crucible furnace with an induction furnace was suggested in order to reduce the manufacturing lead time to meet increasing demand. This new technology will reduce the elapsed time for melting the copper from 60 to 10 minutes and increase the indication furnace capacity. This reduction in melting time will reduce the manufacturing lead time from 376 minutes with the crucible furnace to 226 minutes with the induction furnace. Therefore, the factory’s agility will increase simply with a change in technology infrastructure. Changes in the variety of products could involve the metal spinning machine which is used to produce three dimensional shapes. This machine will help in adding new products. Therefore, changing a machine and/or adding a new machine will help meet the market demand fluctuations and/or the introduction a new product.

Also, changing the method of casting from investment casting to wax casting is very important to achieve a high precision method of molding metals and alloys, which is known as the reengineering process. The current reconfiguration process is not enough to attain high performance result; instead, a reengineering process is needed. This addition is due to the difficult-to- work alloys and their complexity of shape or intricate design. These changes can lead to reducing the manufacturing lead time from 226 to 199 minutes for candlesticks and from 2,175 to 1,390 minutes for chandeliers. 5.3 Analysis of the results The two case studies show that effective changes could be made by adding a new production line with the same design and configuration of the existing production lines and by adding a new version of an extrusion machine with a high production rate. Changes to dies would occur as there are changes from one product to another. Machine reconfiguration levels can be adjusted easily without affecting the whole system. Therefore, less effort and time will be wasted. It can be also observed from these case studies that their applications and analyses will be implemented on flow line manufacturing systems which have a fixed operations sequence and configuration. Therefore, these manufacturing systems, as compared to the CMSs, require less effort (represented by cuts time and cost) to reconfigure, with the exception of the installation of a new production line as in the first case. Updating the needed reconfiguration levels within the coming years is very important and needs to be estimated. Estimating the necessary level of reconfiguration needed can be based on the existing reconfiguration procedures as follows: NRLðt þ 1Þ ¼ w1 ðNALÞ þ w2 ½wPSS F ðPSSÞ þ wPLS ðPLSÞ þ wMHS ðMHSÞ þ w3 ½wNP ðNPÞ þ wPD ðPDÞ þ wDC ðDCÞ

ð19Þ

Equation (19) can be written again with more details and according to their elements as follows: NRLðt þ 1Þ ¼ w1 ½wTE ðNALTE Þ þ wPE ðNALPE Þ þ wMA ðNALMA Þ þ wM ðNALM Þ þ w2 ½wPSS&F ðSSS; RC; RF; RU Þ þ wPLS ðCLÞ þ wMHS ðMHEÞ þ w3 ½wNP ðNPÞ þ wPD ðPDÞ þ wDC ðDCÞ

ð20Þ

Notice that Equation (20) indicates that the period (t) of the NRL(t) can be improved and updated through the following terms: the agility term, manufacturing system design term, and new circumstances term. After the first reconfiguration process through is implemented by the reconfiguration methodology level RML(t), the main reconfiguration issues for the next period (t þ 1) will be generated through NRL(t þ 1), RML(t þ 1), and the performance measurement level (PML(t þ 1)) and so on (Figure 5). 6. Conclusions, contribution, and recommendations for further works In this paper, a new strategy for the reconfiguration of a manufacturing system has been introduced to answer two important questions: “When do we reconfigure manufacturing firms?” and “How do we reconfigure manufacturing firms?” The answer to the first question is explained by measuring the needed reconfiguration level. The answer to the second question is introduced and presented through the reconfiguration methodology.


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Reconfiguration Strategy Period (t+1 )

Period (t )

912 NRL (t)

Figure 5. Stages of the reconfiguration processes

RML (t )

PML (t )

Updating for (t +1 )

NRL ( t+1 )

RML ( t+1 )

PML ( t+1 )

Updating for (t+2 )

A new comprehensive methodology for the reconfiguration of manufacturing systems as a general framework based on the analysis of the reconfiguration issues has been presented. These issues were divided into three main levels: needed reconfiguration level, reconfiguration methodology, and performance measurement. The reconfiguration methodology considers the evaluation of manufacturing systems for reconfiguration, the status of the components of manufacturing systems design, and the new circumstances regarding marketing demand. Applying the proposed reconfiguration methodology in two real case studies is presented and illustrated to explain where areas needed to be reconfigured. The main contribution of this paper is to provide a general framework to reconfigure the manufacturing systems through the identification of the configurability index (needed reconfiguration level) and reconfiguration methodology based on selecting a less complex system at the early design stages while taking into consideration several issues. These issues are centered on production system size and type (cellular system design and configuration) and Material handling systems, such as, vehicles and/or trucks. At times, the relationship between the reconfiguration process and reengineering process should be considered to achieve a high value added change. The authors intend to perform the following future research to enhance the benefits from the current research: .

.

The suggestion build a mathematical model to measure the reconfiguration cost and time because it is difficult to evaluate the exact cost and time in the reconfiguration process. The application of this reconfiguration process (analysis and methodology) with respect to different industries (e.g. discrete product manufacturing, continuous parts manufacturing, food production, assembly lines, petrochemical production, etc.) to estimate the configurability level which represents a major step toward the full validation of reconfiguration strategies.

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Youssef, A.M.A. and El Maraghy, H.A. (2008), “Availability consideration in the optimal selection of multiple-aspect RMS configurations”, International Journal of Production Research, Vol. 46 No. 21, pp. 5849-5882. Zhang, L. and Rodrigues, B. (2009), “Modeling reconfigurable manufacturing systems with colored timed Petri nets”, International Journal of Production Research, Vol. 47 No. 16, pp. 4569-4591. About the author Ibrahim H. Garbie is currently an Assistant Professor in the Mechanical and Industrial Engineering Department at the Sultan Qaboos University (SQU), Sultanate of Oman. Dr Garbie received his PhD in the Industrial Engineering Department at the University of Houston, Texas, USA in 2003, MSc in Manufacturing Processes (1996) and BSc in Mechanical Engineering (Production) (1991) from the Helwan University, Cairo, Egypt. Prior to joining SQU, he has worked as a faculty member at the Helwan University in Egypt. Dr Garbie has taught a variety of courses in the areas of Manufacturing Systems Design, Material Handling Systems, Work Study and Productivity, Operations Research, Maintenance and Reliability Engineering, Engineering Economy, Applied Statistics. His current research area focusses on Manufacturing Systems Design, Complexity Analysis and Measurements in Industrial Enterprises, Lean Production and Manufacturing Leanness, Agile Systems and Agility Measures, Reconfigurable of Manufacturing Systems and Sustainability. He is a Senior Member of IIE. Assistant Professor Ibrahim H. Garbie can be contacted at: [email protected]

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