2.4 Lean Manufacturing System

MSc Thesis (2006)

Lean Scheduling in High Variety, Low Volume Environment Submitted By:

Engr. Aftab Ali Haider

Supervised By:

Engr. Mirza Jahanzaib (Assistant Professor)

Department of Mechanical Engineering Faculty of Mechanical and Aeronautical Engineering University of Engineering and Technology, Taxila

MSc Thesis

Lean Scheduling in High Variety, Low Volume Environment


Approved By

Internal Examiner

External Examiner

(Engr Mirza Jahanzaib)

(Dr Khalid Akhtar)

Department of Mechanical Engineering Faculty of Mechanical and Aeronautical Engineering University of Engineering and Technology, Taxila

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Table of Contents Dedications and Acknowledgment .................................................................................. viii Problem Statement .............................................................................................................. 8 Objectives ........................................................................................................................... 9 1 Introduction ................................................................................................................ 10 1.1 Aim and Motivation .............................................................................................. 11 1.2 Thesis Outline ....................................................................................................... 11 1.3 Assumptions and Approach .................................................................................. 11 2 Manufacturing Systems .............................................................................................. 13 2.1 Introduction ....................................................................................................... 13 2.2 Types of Production ............................................................................................. 14 2.2.1 Jobbing Shop Production .............................................................................. 14 2.2.2 Batch Production ........................................................................................... 14 2.2.3 Mass Production............................................................................................ 14 2.3 Manufacturing System Layouts ............................................................................ 15 2.3.1 Fixed Position Lay Out ................................................................................. 15 2.3.2 Process Layout .............................................................................................. 16 2.2.3 Product Layout .............................................................................................. 16 2.2.4 Cellular Layout ............................................................................................. 17 2.4 Lean Manufacturing System ................................................................................. 17 2.4.1 Lean manufacturing elements ....................................................................... 18 2.5 Waste Reduction ................................................................................................... 27 3.4 Traditional Vs Lean Manufacturing Systems ....................................................... 28 3 Scheduling Theory ..................................................................................................... 30 3.1 Introduction ....................................................................................................... 30 3.2 Scheduling Theory ................................................................................................ 30 3.2.1 Efficient utilization of resources: .................................................................. 31 3.2.2 Low Work in Process .................................................................................... 31 3.2.3 Close Conformance to meet Dead Lines ...................................................... 31 3.3 Production Scheduling .......................................................................................... 31 3.3.1 Scheduling Techniques: ............................................................................... 32 3.4 Job Shop Scheduling ............................................................................................. 33 3.5 Comparison of Lean and Job Shop Systems ......................................................... 33 3.6 Toyota Lean VS Job shop Lean ............................................................................ 35 3.6.1 Product Variety ............................................................................................. 35 3.6.2 Layout ........................................................................................................... 35 3.6.3 Demand Volumes.......................................................................................... 36 3.6.4 Product Design and Process Engineering ..................................................... 36 3.6.5 Availability of Internal Resources ................................................................ 36 3.6.6 Flow line vs. Job shop Scheduling ................................................................ 36 3.6.7 Pull vs. Push of Orders.................................................................................. 36 3.7 Performance Measures .......................................................................................... 36 3.7.1 Manufacturing Lead Time: ........................................................................... 36 3.7.2 Work In Process ............................................................................................ 37 3.7.3 Productivity Improvement ............................................................................ 37 iii

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3.7.4 Performance Measures relating to the Individual Job................................... 37 4 Modeling Tools.......................................................................................................... 40 4.1 Introduction to simulation: .................................................................................... 40 4.1.1 Design and Analysis of simulation experiments ........................................... 41 4.2 Modeling Tool Information .................................................................................. 41 4.2.1 Introduction ................................................................................................... 42 4.3 The primary Template – Arena ............................................................................. 44 4.3.1 Animation: .................................................................................................... 45 4.3.2 Input/output Analyzers.................................................................................. 45 5 Analysis and methodology of Research .................................................................... 46 5.1 Applied methodology............................................................................................ 46 5.2 Flexibility in cell design........................................................................................ 46 5.3 Lean manufacturing cells ...................................................................................... 47 5.4 Case Study -01 ...................................................................................................... 48 5.4.1 Work in Process Inventory (WIP): ............................................................... 48 5.4.2 Average Cycle Times:................................................................................... 49 5.4.3 Tardiness of the Scheduling .......................................................................... 50 5.4.4 Utilization of the Resources: ......................................................................... 53 5.4.5 Under Production / Over Production: ........................................................... 57 5.4.6 Production Volumes .......................................................................................... 59 5.5 Cost analysis of manufacturing Lay Outs: ............................................................ 62 5.4.8 Work Place Area .......................................................................................... 66 5.6 Case Study – 02 .................................................................................................... 68 5.6.1 GT Cell Formation: ....................................................................................... 68 5.6.2 Scope of the Case Study: .............................................................................. 68 5.7 Case Study 03 ....................................................................................................... 80 5.7.1 One Piece Flow Vs Batch Flow: ................................................................... 80 6 Conclusion................................................................................................................. 85 References ......................................................................................................................... 86

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List of Figures Figure 1 Continuum of Manufacturing .........................Error! Bookmark not defined.15 Figure 2 Production Scheduling....................................Error! Bookmark not defined.32 Figure 3 Comparison of WIP ........................................................................................... 48 Figure 4 Lean Cells Vs Existing Set Up .......................................................................... 49 Figure 5 Tardiness in Lean Cell with Loop Conveyors ................................................... 51 Figure 6 Tardiness in Lean Cell with Transporters ......................................................... 52 Figure 7 Tardiness in Lean Cell with Manual Handling.................................................. 53 Figure 8 Utilization of the Resources in the Existing Set Up .......................................... 54 Figure 9 Utilization in Lean Cell with Manual Handling ................................................ 55 Figure 10Utilization in Lean Cell with Transporters II .................................................... 56 Figure 11Utilization Vs Resources Available................................................................... 57 Figure 12Under Production in Existing Set Up ................................................................ 58 Figure 13 Under Production in Lean Cell with Manual Handling.................................... 58 Figure 14 Under Production in Lean Cell with Transporters ........................................... 59 Figure 15 Throughput in Existing Set Up ......................................................................... 60 Figure 16Throughput in Lean Cell with Transporters ...................................................... 61 Figure 17 Throughput in Lean Cell with Manual Handling ............................................. 61 Figure 18 Break Even Analysis ........................................................................................ 66 Figure 19 Work Place Area............................................................................................... 67 Figure 20Comparison of Mean WIP ................................................................................. 69 Figure 21 Mean Flow Time Comparison I ....................................................................... 69 Figure 22Mean Flow Times Comparison II...................................................................... 70 Figure 23 Mean Flow Time Comparison III ..................................................................... 70 Figure 24 Mean Flow Time Comparison IV..................................................................... 71 Figure 25 Mean Flow Time Comparison V ...................................................................... 71 Figure 26 Mean Flow Times Comparison VI ................................................................... 72 Figure 27 Mean Flow Times Comparison VII .................................................................. 72 Figure 28 Mean Flow Times Comparison VIII ................................................................ 73 Figure 29 Production Volumes I ....................................................................................... 73 Figure 30 Production Volumes II ..................................................................................... 74 Figure 31 Production Volumes III .................................................................................... 74 Figure 32 Production Volume IV ..................................................................................... 75 Figure 33 Production Volume V ....................................................................................... 75 Figure 34Production Volume VI ...................................................................................... 76 Figure 35 Production Volume VII .................................................................................... 76 Figure 36 Production Volume ........................................................................................... 77 Figure 37Comparison of Mean Tardiness......................................................................... 77 Figure 38Mean Queue Times I ......................................................................................... 78 Figure 39Mean Queue Times II ........................................................................................ 78 Figure 40 Mean Queue Times III...................................................................................... 79 Figure 41 Mean Queue Times IV ..................................................................................... 79 Figure 42 Mean WIP in One Piece Flow .......................................................................... 80 Figure 43 Mean Flow Time in One Piece Flow ................................................................ 81 v

MSc Thesis


Figure 44 Mean Queue Times in One Piece Flow ............................................................ 81 Figure 45 Utilization of Resources in One Piece Flow.................................................... 82 Figure 46 Queue Lengths in One Piece Flow ................................................................... 82 Figure 47 Throughput in One Piece Flow......................................................................... 83

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List of Tables Table 1 Comparison of Lean and Traditional Manufacturing Methods ........................... 29 Table 2Comparison of Lean with Job Shop...................................................................... 35 Table 3 justification of simulation as Modeling Technique ............................................. 42 Table 4 Lean methodology .............................................................................................. 46 Table 5 Comparison of Average Cycle Times .................................................................. 49 Table 6 Tardiness of the Jobs in Existing Set Up ............................................................. 50 Table 7 Tardiness of Job in Lean Cell with Loop Conveyors .......................................... 51 Table 8 Tardiness of jobs in Lean Cells with Transporters .............................................. 52 Table 9 Tardiness in Lean Cell with Manual Handling .................................................... 53 Table 10 Resource Utilization in Existing Set Up ............................................................ 54 Table 11Resource Utilization in Lean with Manual Handling ......................................... 54 Table 12Resource Utilization in Lean Cell ....................................................................... 55 Table 13 Resource Utilization in Lean Cell with Loop Conveyors .................................. 56 Table 14 Comparison of Throughput ................................................................................ 59 Table 15 Fixed Cost for Existing Set Up .......................................................................... 62 Table 16 Power Requirements for Existing Set Up .......................................................... 63 Table 17 Fixed Cost for Lean Cell .................................................................................... 64 Table 18 Power Requirement for Lean Cell ..................................................................... 65

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Dedications and Acknowledgment

My Respected Father who is a source of inspiration for me

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Problem Statement Heavy Industries Taxila (HIT) is a typical example of a high variety low volume environment. More or less all the shops have same layout. The existing layout these shops are process layout in which all the machine tools are arranged according to their functions. Although organization is rich in all types of resources including manpower, money, machine tools etc yet available facilities are not properly utilized. Dependency of major parts produced within the manufacturing factory is a joint venture of Pakistan and China. The resources are not well utilized and are facing the situation of starvation and saturation. Some of the machine tools are excessively over loaded and others are under utilized. These factors make it difficult for the manufacturing as well as rebuild factory to meet the targets. Mixed model production natured workers assignment for different part products make the schedule very complex. The focus of this research is an industry involved in the rebuild of a main battle tanks. The problems faced during the Rebuild cum manufacturing of this product are mentioned below, 1. The sub components are not manufactured well in time to meet the dead line fixed for the final delivery of these components and hence delay the production of the final component. 2. Some of the manufacturing equipments are over loaded, where as others are under-utilized. There is a need to indicate those machines that are bottlenecks. This may help improve the productivity and balancing of the line. 3. There is no exact calculation about the capacity of the existing set up, which makes it difficult for the higher management to set exact targets. These factors tend to put an extra burden on the middle management to meet the targets. And the consequently the management has to go for extra shifts and overtimes to make the parts for the onward monthly demands. These factors tend to demolish the existing work style and in fact the absence of properly managed resources to meet the timely needs of the industry. The need is to assess the performance measure and suggest improvements in the existing layout that can help improve performance keeping within the resources. If the set up is analyzed physically, it is evident that there is large WIP all the times and there are long buffers at some stations. Research work is needed to analyze the existing environment and then changing it to different configuration to see the effect of different performance measures in this situation. A simulation based model is used to analyze the environment.

MSc Thesis


Objectives The objective of this research study is to schedule the existing set up in such a way that targets are met well in time. Other factors include the proper utilization of the resources, manpower and the space. The ultimate goal is to schedule the rebuild activity on the parameters of the lean scheduling to ensure better results. In traditional production systems, products were manufactured in separate areas (each with a responsibility for a different part of the manufacturing process) and many workers would work on their own, as on a production line. In cell production, workers are organized into multi-skilled teams. Each team is responsible for a particular part of the production process including quality control and health and safety. Each cell is made up of several teams who deliver finished items on to the next cell in the production process. Cell production can lead to efficiency improvements due to increased motivation (team spirit and added responsibility given to cells) and workers sharing their skills and expertise. The focus is to obtain a lean solution of a High Variety Low Volume Environment. The steps towards the lean are as under; 1. Reduce Cycle time by reducing the queue time between manufacturing operations. 2. Reduce WIP inventory by reducing lag time between operations. 3. Reduce Raw material carrying costs. 4. Reduce Finished Goods material storage by using storage space as a critical tooling resource. 5. Improve on time delivery by having Lean Scheduling tell you well in advance, which jobs may finish 6. Make accurate order promise dates. 7. Increase the utilization of key resources. 8. Streamline and standardize the schedule process by having all of the rules in one system. This can be done by eliminating all types of wastes and non value added processes. Lean also stresses on waste reduction by analyzing the existing set up to highlight all types of wastes.

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1


Introduction

Heavy Industries Taxila (HIT) is backbone of Pakistan army. The birth of HIT took place in 1971 when Project-711 was established in Taxila with Chinese assistance mainly to rebuild the T-59 Tank fleet of the Pakistan Army. With the passage of time it came to be known as Heavy Rebuild Factory (HRB) that was instrumental in imparting invaluable know-how and experience that made further expansion possible. In the month of September, 1992 reorganization took place in this industrial complex and it was re-named as Heavy Industries Taxila. The main activities of HIT are (1) re-build and up gradation of Armored Vehicles of eastern as well as of western origin, (2) progressive manufacture of tanks and armored personnel carriers (APCs) and (3) progressive manufacture of tank guns. In order to accomplish its assigned tasks, HIT employs a highly trained and skilled work force of around 6000. HIT is a combination of multiple industries that has grown into a large military complex. It consists of six major production units and there support facilities such as Heavy Rebuild Factory T-Series and Heavy Rebuild Factory M-Series (rebuild facilities), APC Factory, Tank Factory and Gun Factory (manufacturing facilities), Development Engineering Support Components Manufacture (DESCOM) and Evaluation, Training and Research Organization (ETRO) (engineering support facilities) and Project MBT-2000, Al-Khalid (Tank production factory). This factory has the distinct honor of rebuilding the first T-59 tanks in 1980 and at present it also upgrades T-59s to the T-59M and Al Zarrar version. All tanks are usually called in for rebuild after 10 years of active life after which the tank is taken apart and it is rebuilt with numerous upgraded features being added. Project MBT 2000 which is dedicated to the development of the Al-Khalid Tank is a significant step in the direction of self-attainment. The extensive scope of HIT activities (or that of any other industrial manufacturing unit for that matter) cannot even begin to achieve its goals unless the back-up of an efficient general engineering support to all its manufacturing and rebuild factories is put in place. Indigenization is high on the list of priorities at HIT and in order to implement HITs deletion program, DESCOM has successfully produced a number of components indigenously, this is a major step towards self-reliance. This process has helped HIT to absorb technologies for the future and save considerable amount of foreign exchange, today more than 7500 components of differing types are manufactured locally by HIT while another 7500 components of various categories are being produced by numerous vendors associated with HIT. The vendor industry is particularly encouraged in the production of local equipment and DESCOM continues to provide them with technical assistance and guidance at all stages of production and manufacture. These combined dedicated efforts have now resulted in HIT achieving 81% deletion by variety in the components of T-59 Tanks, 56% in T-69 Tanks and 40% in APCs. HIT has become a very important industrial base and is playing a definite and potent role in national selfreliance.

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1.1


Aim and Motivation

Manufacturing has ever been a source of rapid development all over the world. Only those nations can prosper in 21st century who has hi- tech manufacturing industry to meet the challenges of the globalization. The importance of the manufacturing in daily life can’t be denied. The China has got prosperity within last decade only due to the advancement in manufacturing The focus is to get a Lean solution of a High Variety Low Volume Environment. The steps towards the Lean are as under; 1. Reduce Cycle time by reducing the queue time between manufacturing operations. 2. Reduce WIP inventory by reducing lag time between operations. 3. Reduce Raw material carrying costs. 4. Reduce Finished Goods material storage by using storage space as a critical tooling resource. 5. Improve on time delivery by having Lean Scheduler tell you well in advance, which jobs may finish 6. Make accurate order promise dates. 7. Increase the utilization of key resources. 8. Streamline and standardize the schedule process by having all of the rules in one system.

1.2

Thesis Outline

Chapter 1 gives a short introduction of Lean Scheduling and describes the research overview. Chapter 2 gives details of the manufacturing Systems. It also briefly describes manufacturing layouts. It also gives description of the lean systems and the basic of the lean manufacturing system and also describes the elements of the lean thinking. Chapter 5 describes focus on wastes in Lean manufacturing. Chapter 3 describes scheduling theory with an introduction to production scheduling. Chapter 4 is about the modeling and common modeling softwares used for simulation purpose. It also briefly introduces Arena 3.0 used in this research. Chapter 5 is to analyze the case studies and the methodology used for research work. Chapter 6 gives the conclusion of the research work.

1.3

Assumptions and Approach

To simplify the analysis, the following assumptions are made for the rebuild activity; 1. Set up Times are either nominal or these are included in the Processing Times. 2. The fixtures are designed such that the clamping and holding is not a problem. 3. There are quick changeover techniques.

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MSc Thesis


4. The tool magazine is designed for all the parts and tool is changed with out any interruption within 10 seconds of the processing time.

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2 2.1

Manufacturing Systems

Introduction

Manufacturing is the economic term for making goods and service that will be available to satisfy human wants and needs. Manufacturing is creating value by applying useful mental and /or physical labor and, thus converting raw material into useful products demanded by customers. Manufacturing processes are combined to form manufacturing systems. Manufacturing systems take input and produce products for customers. Production systems include and service manufacturing systems. Thus a production system refers to the total company and includes manufacturing systems as well. There are two basic categories of industrial plant: continuous process industries and discrete parts manufacturing. Continuous process industries involve the continuous production of a product, often using chemical as well as physical or mechanical means (e.g. the production of fertilizers or sugar). Discrete parts production involves the production of individual items. Of course one of the most important factors that determine the type of the manufacturing is the type of the products that are made. If we limit the discussion only to the discrete products, the quantity produce by a factory has a very significant impact on the way manufacturing is organized. Traditional mass and batch manufacturing environment were mainly characterized by few product varieties, long time to market, long product life cycles, and product demand curves depicted by well defined growth, maturity and decline periods. The annual parts or products produced in a factory can be classified into three ranges: Low production: Quantities in the range of 1 to 100 units per year Medium Production: Quantities in the range of 100 to 10000 units annually High Production: Quantities are 10,000 to millions of units Some plants produce a variety of different product types, each type being made in low or medium quantities. Other plants specialize in high production of only one product type. Product variety refers to the different product designs or types that are produced in a plant. The product variety may be hard or soft. Product variety is termed as hard when the products differ substantially. The difference between the motor bike and motor car is Hard. Product variety is referred to as soft when there is only small difference between products, such as the difference between Mobile Sets models being made on the same production lines. The variety between different product categories tends to be hard; the variety between different models within the same product category tends to be soft. There is an inverse co-relation between product variety and product quantity in terms of factory operations. When product variety is high, production quantity tends to be low;

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and vice versa. In general, a given factory tends to be limited to the product variety value that is co-related with that production quantity.

2.2

Types of Production

The three basic types of the discrete type manufacturing are; a) Jobbing Shop Production b) Batch Production c) Mass Production

2.2.1

Jobbing Shop Production

The main characteristic of jobbing shop production is very low volume production runs of many different products. These products have a very low level of standardization in that there are few, if any, common components. To produce the different products, the manufacturing firm requires a highly flexible production capability. This implies flexible equipment capable of performing many different tasks, as well as highly skilled work force. Jobbing shops normally operate a Make To Order or Engineer To Order policy. A typical example of jobbing shop is a subcontract machine shop.

2.2.2

Batch Production

Batch production’s main characteristic is medium volume production runs of a range of products. Batch production is defined as the production of a product in small batches or lots by a series of operations, each operation typically being carried out on the whole batch before any subsequent operation is started on that batch. The production system must be reasonably flexible and uses general purpose equipment in order to accommodate varying customer requirements and fluctuations in demand. Batch production can be seen as a situation which lies between the extremes of the pure jobbing shop and pure mass production, and where the quantities required are insufficient to justify mass production. Because of the large variety of jobs involved, batch production has much of the complexity of the jobbing shop. A typical example of batch production is the manufacture and assembly of machine tools.

2.2.3

Mass Production

The major characteristic of mass production is large volume production runs of relatively few products. All products are highly standardized. Typically, demand is suitable for the products and the product design changes very little over the short to medium term. The production facilities consist of highly specialized, dedicated and associated tooling. Although these machines are extremely expensive, the cost is associated over very long production runs. The term hard automation or Detroit style automation was coined to describe the type of automation associated with mass production. It is hard in

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the sense that the automation is dedicated and very inflexible. Mass production fits the category of a Make to Stock manufacturing environment.

2.3

Manufacturing System Layouts

A layout is the physical configuration of departments, workstations, and equipment in the entire conversion process. It is the special arrangement of physical resources used to create the product or service. The right layout for an organization improves productivity, the quality of the product or service, and delivery rates. The layout decision is very important strategically for any organization to stay competitive in the present era. There are basically four types of layouts for discrete type of manufacturing set up 1. Fixed Position Layout 2. Process Layout 3. Product Layout 4. Cellular Layout

Figure 1 Continuum of Manufacturing

2.3.1

Fixed Position Lay Out

In this type of the lay out the product remains in a single location during the entire fabrication process. Workers and processing equipment are brought to the product, rather than moving the product to the equipment. In the pure situation, the product remains in a single location, at least during its final assembly. Examples of such products include

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ships, sub marines, aircrafts, loco motives, Battle tanks and heavy machinery. In actual practice, these items are usually built in large modules at single location and then the completed modules are brought together for final assembly using large capacity cranes.

2.3.2

Process Layout

In Process layout the equipment is arranged according to its function or type. The Lathes are in one department, the milling machines are in another department, and so on. Different parts, each requiring a different operation sequence, are routed through the departments in the particular order needed for their processing usually in batches. The process layout is noted for its flexibility and it can accommodate a great variety of alternative sequences for different part configurations. Its disadvantage is that the machinery and methods to produce a part are not designed for high efficiency. Much material handling is required to move parts between the departments, so in-process inventory can be high. The process or functional layout is suitable for small, discreteparts manufacturing and machines are grouped into departments according to type of operation. 2.3.2.1.1

Advantages of Process Lay out:

Some of the major advantages of the process layout are; 1. Work schedule is more flexible 2. Deep knowledge of the process 3. Common tooling and fixtures 2.3.2.1.2

Disadvantage of Process Lay Out:

Some of the major disadvantages are; 1. 2. 3. 4. 5. 6.

Spaghetti flow-everything gets all tangled up Difficult to automate WIP is large (cost in inventory and storage space), High material handling cost, Larger batches are made than are required (to justify setup), Difficulty in maintaining control of parts, 7. Highest skill level required from operators.

2.2.3 Product Layout Multiple stations arranged in sequence, and the parts or assemblies are physically moved through the sequence to complete the product. The workstations consist of production machines and/or workers equipped with specialized tools. The collection of stations is designed specifically for the product to maximize efficiency. This type of the layout is

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called a Product Layout, with the workstations arranged into a long line or series of the combined line segments. Powered conveyor is usually used to move the work between the workstations. At each station, a small amount of the total work is completed on each unit of product.

2.2.4 Cellular Layout A Cellular manufacturing comprises of cells specialized in the production of a given set of similar parts or products according to the principle of the Group Technology. If the variety is soft in case of medium production, extensive changeover between one product and the next product is undesirable. It is often possible to configure the equipment so those groups of similar parts can be made on the same equipment without significant lost time for changeovers. The processing or assembly of different parts or products is accomplished in cells consisting of several workstations or machines. The term cellular manufacturing is often associated with this type of manufacturing. 1.2.4.1.1

Advantages of Cellular Layout:

Advantages of the cellular layout are; 1. Control is simplified 2. Highly flexible 2.2.4.2

Disadvantages of Cellular Layout

Some of the disadvantages of the Cellular layout are; 1. There is a need to know about many other relevant processes 2. Set up remains a point of concern

2.4

Lean Manufacturing System

Lean manufacturing is the systematic elimination of waste, and the implementation of continuous flow concepts and customer pull. Lean is the best management system for satisfying customers on delivery, quality and price. Lean Manufacturing can be defined as: "A systematic approach to identifying and eliminating waste (non-value-added activities) through continuous improvement by flowing the product at the pull of the customer in pursuit of perfection." Or ―Lean Production is a term used to describe JIT and the Toyota Production System.‖

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The Production System Design Laboratory (PSD), Massachusetts Institute of Technology (MIT) states that ―Lean production is aimed at the elimination of waste in every area of production including customer relations, product design, supplier networks and factory management. Its goal is to incorporate less human effort, less inventory, less time to develop products, and less space to become highly responsive to customer demand while producing top quality products in the most efficient and economical manner possible.‖ "Lean" because it uses less of everything compared with mass production--half the human effort in the factory, half the manufacturing space, half the investment in tools, half the engineering hours to develop a new product in half the time. Also, it requires keeping far less than half the needed inventory on site, results in many fewer defects, and produces a greater and ever growing variety of products. Womack et al., 13. Japanese manufacturers re-building after the Second World War were facing declining human, material, and financial resources. The problems they faced in manufacturing were vastly different from their Western counterparts. These circumstances led to the development of new, lower cost, manufacturing practices. Early Japanese leaders such as the Toyota Motor Company's Eiji Toyoda, Taiichi Ohno, and Shingeo Shingo developed a disciplined, process-focused production system now known as the "Toyota Production System", or "lean production." The objective of this system was to minimize the consumption of resources that added no value to a product. The "lean manufacturing" concept was popularized in American factories in large part by the Massachusetts Institute of Technology study of the movement from mass production toward production as described in ―The Machine That Changed the World‖, (Womack, Jones & Roos, 1990), which discussed the significant performance gap between Western and Japanese automotive industries. This book described the important elements accounting for superior performance as lean production. The term "lean" was used because Japanese business methods used less human effort, capital investment, floor space, materials, and time in all aspects of operations. The resulting competition among U.S. and Japanese automakers over the last 25 years has lead to the adoption of these principles within all U.S. manufacturing businesses.

2.4.1 Lean manufacturing elements Waste elimination continuous one-piece flow and customer pulls are the basic elements of lean manufacturing. Focusing these elements in the areas of cost, quality, and delivery forms the basis for a lean production system.    

Value stream mapping One Piece flow 5S system Set up reduction/quick change over techniques 18

MSc Thesis

  


Pull/ KANBAN Cellular manufacturing Total productive maintenance

2.4.1.1

Values Stream mapping

The value of a business is the sequence of steps that a company performs in order to satisfy a customer need. In every value stream, a 50 –70 % reduction in the number of steps in the process can be achieved. The first step a company must take to change their value stream is to determine its lean status by identifying its deficiency gaps and areas for waste / cost reductions. Lean manufacturing is a fundamental enterprise transformation that must be approached to as a total organizational and structural transformation. Value stream mapping is a good way to train staff to find waste, identify the root cause, and prepare a strategic plan for its elimination. Value stream mapping is a method of visually mapping a product’ s production path (materials and information) from door to door. VSM can serve as starting point to help management, engineers, production associates, schedulers, suppliers, and customers recognize waste and identify causes. The process includes physically mapping your current state while also focusing on where you want to be, or your future state blue print, which can serve as the foundation for other lean improvement strategies. A value stream is all the actions (both value added and non-value added) currently required to bring products through the main flows essential to every product.  The production flow from raw material into the arms of the customer  The design flow from concept to launch Taking a value stream perspective means working on the big picture, not just individual processes, and improving the whole, not just optimizing the parts Value stream mapping is a pencil and paper tool that helps you to see and understand the flow of material and information as a product makes it way through the value stream. The meaning is simple: Follow on products production path from customer to supplier, and carefully drawing a visual representation of every process in the material and information flow. Then ask a set of key questions and draw a future state map of how the value should flow. Within the production flow, the movement of material through the factory is the flow that usually comes to mind. But there is another flow of information that tells each process what to make or to do next. One must keep both of these flows.

Value stream mapping can be a communication tool, a business planning tool, and a tool to manage your processes. The first step is drawing the Current State, which is done by gathering information on the shop floor. This provides the information needed to map a future state the final step is to prepare and begin actively using an implementation plan that describes on one page, how you plan to achieve the future state.

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More and more organizations with successful shop floor lean efforts are also applying value stream mapping methods and lean principles to administrative areas. Value stream mapping provides a simple, yet thorough methodology that relies on relevant data analysis and display. It links reporting requirements, metrics, people and lean tools to sustain improvements and promote process learning. It gives managers and employees the same tool and language to communicate.

2.4.1.2

5 s System

5 s System is an approach to improvement within a facility or manufacturing plant that focuses on organization’s cleanliness and standardization to improve profitability, efficiency, service and safety. The basis of a Five-S system is not very complicated. They are actually based on common sense. 5S stands for 5 Japanese words all starting with S. it is not necessary to remember 5S in Japanese. What is important is to understand what does it means and practice it rather than just memorizing the words Japanese

English

SEIRI SEILTON SEISO SEIKETSU SHITSUKE or ordered

SORT SET IN ORDER SHINE STANDARDISE SUSTAIN

2.4.1.3

Brief Explanation Take out necessary items and dispose arrange necessary items in good order Clean you Work place Maintain High standard of housekeeping Do things spontaneously without being told

Visual Control

The intent of a visual factory is that the whole workplace is set up with the signs, labels, color coded markings etc. such that anyone unfamiliar with the process can, in a matter of minutes, know what is going on, understand the process and know what is being done correctly and what is out of place There are two types of application in visual factory, displays and controls. 



A visual display relates information and data to employees in the area. For example, Charts showing the monthly revenues of the company depicting a certain type of quality issue those group members should be aware of. A visual control is intended to actually control or guide the action of the group members, Examples of controls are readily apparent in society: stop signs, handicap parking signs, no smoking signs etc.

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   

   


This is contrast to previous workplace rules, which dictated that performance data should be retained as management secrets, for the sole consumption of managers who knew what do with the members. Visual controls describe workplace safety, production throughput, material flow, quality metrics or other information The most important benefit of a visual factory is that it shows when something is out of place or missing. Visuals Displays and controls can help keep things running as efficiently as they were designed to run. The efficient design of the production process that results from lean manufacturing carries with it a set of assumptions. The process will be successful as it was designed to be as long as the assumptions hold true. A factory with expensive visual display and control applications will allow employees to immediately know when one of the assumptions has not held true. Audio signals in the factory are also very important because these signal malfunctioning equipment, sound warnings before the start of machine operation, or other useful information. Visual management is an important support for cellular manufacturing. Visual management techniques express information in a ways that can be understood quickly be everyone. /sharing information through visual tools helps production running smoothly and safely. Shop floor teams are often involved in devising and implementing these tools through 5S and other improvement activities. Visual information can also help prevent mistakes. Color-coding is a form of visual display often used to prevent errors. Shaded pie slices on a dial gauge tell the viewer instantly when the needle is out of the safe range. Matching color marks is another approach that can help people use the right tool or assemble the right part.

2.4.1.4

One piece Flow

One piece flow (also commonly referred to as continuous flow manufacturing) is a technique used to manufacture components in a cellular environment. The cell is an area here everything that is needed to process the part is within easy reach and no part is allowed to go to the next operation until the previous operation has been completed. The goal of the one-piece flow is to make one part at a time correctly all the time to achieve this without unplanned interruptions to achieve this without lengthy queue times.    



Tasks are reduced to their simplest components Opportunities for machine or operator error are reduced Done correctly, there is a continuous flow of activities between the shop operators and manufacturing product This is a generative manufacturing method created to continuously increase output, improve quality, and grow sales and profits, without the need for constantly enlarging production or support staff. One piece flow is an extremely efficient way to manufacture goods, provided the correct physical structures have been set up to support its particular needs. 21

MSc Thesis


2.4.1.5

Pull /KANBAN

The concept of pull is lean production means to respond to the pull, or demand of the customer. Lean manufacturers design their operations to respond to the ever-changing requirements of the customer. Those able to produce to the pull of customers do not need to manufacture goods that traditional batch and queue manufacturers must rely on. The planning for delivery of product to customers is less troublesome, and demand becomes more stable if customers have confidence in knowing hat they can get what they want hen they want it. Kanban is a Japanese word that means instruction card. Kanbans are manual pull devices that allow an efficient means to transfer parts from one department to another and automatically re order products using minimum / maximum inventory levels. A Kanban is a signal, such as an empty container returned to the start of the assembly line, which signals the need for replenishment of materials to as user.  Kanbans are used in pull manufacturing systems, where product is manufactured to the pull of the market oriented demand.  Kanban systems must be convenient and easy to use.  Pull system react to needs, they don’t anticipate them  Successfully deployed Kanbans deliver the right amount of material to the right place exactly when it is needed.  Several pull techniques can be used for different products at the same work site.  Great speed can be achieved in manufacturing, and product is not manufactured when a need doesn’t exist.  A Kanban or pull system means providing the workers with what they need when they need it- tools, software, capital equipment, access, feed back or the opportunity to participate.  Kanbans or cards are used when the move time and distance between producing and consuming departments are significant.  Each card controls a specific quantity of parts  Cards are returned to the producing department after parts are consumed triggering production of the next batch.  Single card system are used when the products are able to be re supplied prior to running out  Multiple card systems are used if the producing work site produces several products or if the lot size is different from the move size.  Physical Kanbans, Kanban squares, or shelf reserves are used hen the producing and consuming work sites are physically adjacent.  Must have relatively close proximity  Used when major queue of parts is maintained in the producing department. Maximum and minimum queue sizes can co ordinate production between work sites with different capacities.  Physical area holds enough space to cover variations in rates  Goal of the producing department is to fill the space reserved for the part.

22

MSc Thesis


2.4.1.6

Set up reduction / quick change over techniques

Customers today want a variety of products in just the quantities they need. They expect high quality, a good price and speedy delivery. Producing to customer requirements means getting batch processes to produce in small lots. Doing this usually creates a need to reduce set up times. The goal of setup reduction and changeover improvements should be to develop a production system that gets as close as possible to making only what the customer wants, when the customer wants it, throughout the production chain. The results being a strong, flexible manufacturing operation that is adaptable to changes. Many companies produce goods in large lots simply because long changeover times make it costly to frequently change products. Large lot production has several disadvantages  Inventory waste: sorting out what is not sold costs money and ties up company resources without adding any value to the product.  Delay: customers must wait for the company to produce entire lots rather than just the quantities a customer needs  Declining quality: sorting unsold inventory increases the chance that it will have to be scrapped or reworked, which adds cost to the product. When methods are in place to accommodate quick changeover, setups can be done as often as needed. This means you can make products in smaller lots, which has many advantages    

Flexibility: you can meet changing customer needs without the expenses of excess inventory Quick delivery: small lot production means less lead-time and fewer customers waiting time Better quality: less inventory storage means fewer storage-related defects. Quick changeover methods lower defects by reducing setup errors and eliminating trial runs of the new product. Higher Productivity: shorter changeovers reduce downtime, which means a higher equipment productivity rate.

First look at how you currently perform set up operations before you can improve them. Three preliminary steps involved in a set up analysis include:   

Video aping the entire set up operation Asking setup personnel to talk about what they do Studying the time and motions involved in each step of the set up

Set up improvement activities can be implemented in three stages   

Distinguishing between internal and external set ups Converting internal set ups to external set ups Streaming all aspects of the set up operation

23

MSc Thesis


As a broad term set up covers not only the replacement of tooling and production parts, but also other operations, such as the revision of standards and the replacements of assembly parts and other materials

2.4.1.7

Cellular manufacturing

Cellular manufacturing is an approach that helps build a variety of products with as little waste as possible. Equipment and workstations are arranged in a sequence that supports a smooth flow of materials and components through the processes, with minimal transport or delay.  A cell consists of the people and the machines or workstations required for performing the steps in a process or process segment, with the machines arranged in the processing sequence.  Arranging people and equipment into cells helps companies achieve to important goals of lean manufacturing. 

One piece flow: one piece flow is the state that exists when products move through a process one unit at a time, at a rate determined by the needs of the customer. The goal of one-piece flow is to make one part at a time all the time, without unplanned interruptions and to achieve this without lengthy queue times



High variety productions: given the fact that customer expect variety and customization, as well as specific quantities delivered at a specific time, it is necessary to remain flexible enough to serve their needs. Cellular manufacturing offers companies the flexibility to give customers the variety they want. It does this by grouping similar products into families that can be processed on the same equipment in the same sequence. It also encourages companies to shorten the time required for changeover between products. This eliminates a major reason for making products in large lots that changeover take too long to change the product type frequently. Converting a factor to cellular manufacturing means eliminating waste from processes as well from operations Cellular manufacturing can help make company more competitive by cutting out costly transport and delay, shortening the production lead time, saving factory space that can be used for other value adding purposes, and promoting continuous improvements by forcing the company to address problems that block low inventory production.

 



Cellular manufacturing help employees by strengthening the company’s competitiveness, which helps support job security. It also makes daily production work go smoother by removing the clutter of WIP inventory, reducing transport and handling, reducing the walking required and addressing causes of defects and machine problems.  Common benefits associated with cellular manufacturing include;

24

MSc Thesis


      

WIP reduction Space utilization Lead time reduction Productivity improvement Quality improvement Enhanced team work and communication Enhanced flexibility and visibility

2.4.1.8

Total productive maintenance

Total productive maintenance is an initiative for optimizing the effectiveness of manufacturing equipment. TPM is team based productive maintenance and involves every level and function in the organization from top executive to the shop floor. The goal of TPM is profitable PM, this requires you to not only prevent breakdowns and defects but to do so in ways that are efficient and economical. To achieve this goal you will need to master four techniques:    

Preventive maintenance: preventing breakdowns Corrective maintenance: improving or modifying equipment to prevent breakdowns or to make maintenance easier. Maintenance prevention: designing and installing equipment that needs little or no maintenance Breakdown maintenance: repairing after breakdowns occur

Some of the facts and concepts of TPM are;    

 

TPM addresses the entire production system life cycle and builds a concrete, shop floor based system too prevent all losses. Its aims include the elimination of all accidents and breakdowns. Everyone participates in TPM, from top executive to shop floor employees TPM achieves zero losses through overlapping team activities A TPM development program consists of activities aimed specifically at eradicating the six big losses that sap efficiency and drain productivity.  Breakdowns  Setup and adjustment losses  Idling and minor stoppages  Reduced speeds  Defects and rework  Start up yield losses Team activities are basic to TPM. Teams at top management, middle management, and shop floor levels carry out TPM activities. Each type of team has its own objectives and part to play. Safety is a cornerstone of TPM, the basic principle behind TPM safety activities is to address dangerous conditions and behavior before they cause accidents.

25

MSc Thesis








Workplace organization and discipline, regular inspections and servicing, and standardization of work procedures are the three basic principles of safety. All are essential elements in creating a safe workplace.

Sustaining smooth production means avoiding equipment breakdowns and defects. You will need to install suitable equipment in the first place and keep it functioning properly through three types of activities.  Daily maintenance (cleaning, checking, lubricating, and tightening) to prevent deterioration.  Periodic inspections or equipment diagnosis to measure deterioration  Restoration to correct and recover from deterioration Achieving the goals of TPM requires activities in eight key areas  Focused improvements to make equipment more efficient  Autonomous maintenance activities  Planned maintenance for the maintenance department  Technical training in equipment maintenance and operation  An early equipment management program  Quality maintenance activities  A system for increasing the efficiency of administrative and support functions  A system for management of safety and environmental issues

The following activities are the most common for implementing TPM effectively. They form the foundation to support any TPM effort. Not all of these strategies are implemented at once. You will develop a sequence that fits situation

2.4.1.9

Standardized work

Standard work is a term used to systematize how a part is processed, and includes manmachine interactions and studies of human motions. Operations are safely carried out with all tasks organized in the best-known sequence and by using the most effective combination of resources 1. 2. 3. 4.

People Materials Methods Machines

Some of the facts and concepts are;  

Manufacturing engineers break down each operation into small pieces, making certain that each work is given all the tools to make the part quickly and with the highest quality The process is documented in writing, with photographs and videos, and examples of defective products nearby. This is done to eliminate errors that waste time and money, and ensure reproducibility from operator to operation

26

MSc Thesis




One of the challenges of senior management is to ensure that everyone in the organization understands the challenges of the workplace, accepts the performance metrics and believes in the company’s values, mission and vision. Standardization must occur not only within the area, but across the entire plant as well. This will include paint and color standards for safety elements, equipment operation instructions, floor markings, buildings interior and exterior, material labeling, etc. By creating standards and defining procedures, there will be commonality across the entire organization. Any type of business will benefit from this focused improvement effort. Those that want dramatic short-term improvement in a critical area or process and those who want a hand on approach to improvement ill find this tool to be highly effective.

2.5

Waste Reduction

The aim of Lean Manufacturing is the elimination of waste in every area of production including customer relations, product design, supplier networks, and factory management. Its goal is to incorporate less human effort, less inventory, less time to develop products, and less space to become highly responsive to customer demand while producing top quality products in the most efficient and economical manner possible. The seven categories of non-value added wastes are over production, inventory, transportation, waiting, motion, over processing and correction. Over production is a source of waste for most firms and is referred to as the batch and queue mode of operation. This large batch-processing mode is an outdated paradigm. Another problem with large batches is that there is no connection between the pace of production and the pace of demand. Reduced lot sizes with the quick set up capability are paradigm of the 21st century. Producing various models in small lots improves the responsive ness to customers and flexibility to respond to the changes in demand. The smaller the lot means the smoother the process flow. The following five areas drive lean manufacturing / Production: cost, quality, delivery, safety and morale. Lean manufacturing views continuous, one piece flow as the ideal and emphasizes optimizing and integrating systems of machines, materials, people, and facilities. Continuous flow follows the produce one by one as efficiently as possible ideology. There are seven categories of muda (wastes) as mentioned above:       

Over Production ahead of demand Waiting for the next process step of the information Transporting materials unnecessarily Over and non value added processing Inventory that is more than bare minimum Motion by employees that is unnecessarily Producing non-conforming Parts

The amazing facts is that at least 95 % of the cycle time in a non lean factory or office is consisted of non value added activities.

27

MSc Thesis


Lean thinking or principle can be applied in service industry as well as in manufacturing industry to reduce lead-time, improve quality and productivity by eliminating wastes in the system. ―Essentially, a "waste" is anything that the customer is not willing to pay for. ―The worst of all the 7 wastes is overproduction because it includes in essence all others and was the main driving force for the Toyota JIT system; they were smart enough to tackle this one to eliminate the rest.

3.4

Traditional Vs Lean Manufacturing Systems

For years manufacturers have created products in anticipation of having a market for them. Operations have traditionally been driven by sales forecasts and firms tended to stockpile inventories in case they were needed. A key difference in Lean Manufacturing is that it is based on the concept that production can and should be driven by real customer demand. Instead of producing what you hope to sell, Lean Manufacturing can produce what your customer wants...with shorter lead times. Instead of pushing product to market, it's pulled there through a system that's set up to quickly respond to customer demand. Lean organizations are capable of producing high-quality products economically in lower volumes and bringing them to market faster than mass producers. A lean organization can make twice as much product with twice the quality and half the time and space, at half the cost, with a fraction of the normal work-in-process inventory. Lean management is about operating the most efficient and effective organization possible, with the least cost and zero waste. Table1 compares the Lean Cell with the Traditional Manufacturing and Job Shop respectively

28

MSc Thesis


MANUFACTURING METHODS

TRADITIONAL PRODUCTION

LEAN PRODUCTION

Production schedules are based Forecast — product is pushed Customer Order — product is on… through the facility pulled through the facility Products manufactured to…

Replenish finished goods inventory

Fill customer orders (immediate shipments)

Production cycle times are…

Weeks/months

Hours/days

Manufacturing lot size quantities are…

Large, with large batches moving between operations; product is sent ahead of each operation By department function

Small, and based on one-piece flow between operations

Quality is assured…

Through lot sampling

100% at the production source.

Workers are typically assigned…

One person per machine

With one person handling several machines

Worker empowerment is…

Low — little input into how operation is performed

Inventory levels are…

High — large warehouse of finished goods, and central storeroom for in-process staging Low — 6-9 turns pr year or less

High — has responsibility for identifying and implementing improvements Low — small amounts between operations, ship often

Plant and equipment layout is…

Inventory turns are…

By product flow, using cells or lines for product families

High — 20+ turns per year

Flexibility in changing manufacturing schedules is…

Low — difficult to handle and High — easy to adjust to and adjust to implement

Manufacturing costs are…

Rising and difficult to control Stable/decreasing and under control

Table 1 Comparison of Lean and Traditional Manufacturing Methods

29

MSc Thesis


3 3.1

Scheduling Theory

Introduction

The main characteristic of jobbing shop production is very low volume production runs of many different products. These products have a very low level of standardization in that there are few, if any, common components. To produce the different products, the manufacturing firm requires a highly flexible production capability. This implies flexible equipment capable of performing many different tasks, as well as highly skilled work force. Jobbing shops normally operate a Make To Order or Engineer To Order policy. A typical example of jobbing shop is a subcontract machine shop. The type of production facility associated with the quantity range of 1 to 100 units per year is the job shop, which makes low quantities of specialized and customized products. Such a manufacturing set up is also referred to as Make to Order or Contract shop or Customized production system. The products are typically complex, such as space capsules, aircraft and special machinery. Job shop production can also include fabricating the component parts for the products. Customer orders for these kinds of items are often special, and repeat orders seldom occur. The equipment used in the job shop is general purpose and the labor force is highly skilled. If the product is large and heavy, and therefore difficult to move in the factory, it typically remains in a single location, at least during its final assembly. Workers and processing equipment are brought to the product, rather than moving the product to the equipment. This type of the lay out is referred to as fixed position lay out. In the pure situation, the product remains in a single location, at least during its final assembly. Examples of such products include ships, sub marines, aircrafts, loco motives, Battle tanks and heavy machinery. In actual practice, these items are usually built in large modules at single location and then the completed modules are brought together for final assembly using large capacity cranes. The individual parts that comprise these large products are often made in factories that have a process lay out, in which the equipment is arranged according to the function or type. The major objectives of the job shop production are;   

Reduce the set up time Reduce processing time Reduce WIP

3.2

Scheduling Theory

The scheduling theory is concerned primarily with mathematical models that relate to the scheduling theory function and the development of useful models and techniques have been the continuing interface between theory and practice. The theoretical prospective is predominantly a quantitative approach, one that attempts to capture problems structure in concise mathematical form. In particular, this quantitative approach begins with a conversion of decision-making goals in to an explicit objective function with explicit

30

MSc Thesis


constraints. Ideally the objective function should consist of all costs in the system that depends on scheduling decisions. in practice however, such costs are often difficult to measure and identify completely. However, there are three types of decision making goals seem to be prevalent in scheduling.

3.2.1 Efficient utilization of resources: It is scheduling the parts to maintain high level of labor, machines and space utilization.

3.2.2 Low Work in Process Scheduling should allow jobs to b processed at rapid rate resulting in low levels of WIP inventory.

3.2.3 Close Conformance to meet Dead Lines Scheduling should ensure that due dates are met every time through shorter lead times. Frequently, important cost related measures of system performance (such as machine idle time, job waiting time or job lateness etc) could be taken as substitute for total system cost. Two kind of feasibility constraints are commonly found in scheduling problems. First there are limits on the capacity of available resources and, second, there are technological restrictions on the order in which tasks can be performed. A solution to a scheduling problem is any feasible resolution of these two types of constraints. In other words, the essence of scheduling problems gives rise to; 1. Allocation decisions 2. Sequencing decisions The theory of scheduling essentially includes a variety of techniques that are useful in solving scheduling problems. Extensive research has failed to arrive at a single priority rule which results in superior performance as measured by all criteria for all job shops and set of jobs. Rather it shows that one rule may be better than others depending upon the measure of performance selected and the characteristics of the job shop and jobs. For example, the best rule for maximizing job completed on schedule will not necessarily maximize machine utilization. Or a rule which is effective in a lightly loaded shop becomes infeasible when applied in a more heavily loaded. Some researchers have obtained improved results by combining the simple priority rules The list of optimized criteria includes mean time in the shop, mean idle time of the machines, mean lateness of the job, man tardiness of the job, mean earliness of jobs, mean queue time, mean number of jobs in the system, mean number of jobs in the system, Percentage of jobs late, make span.

3.3

Production Scheduling

Production scheduling focuses on scheduling individual production units or shops. A production unit is a production department, which on short term is self–contained regarding the use of resources. The production unit is responsible for the timely

31

MSc Thesis


production of a specific set of products. The place of the production unit in the production control structure is illustrated Figure. The input of scheduling comes from the planning function (for example an MRP standard software package) and consists of material requirements in time. The scheduling function can then be stated as follows: for each capacity resource, determine the points in time in which manufacture will be executed, under the following constraints: Finite capacity resources, precedence relations (routings), and start– and due–dates of work–orders. The scheduling function should optimize certain logistic goals, e.g., resources utilization, set– up times, stock costs, throughput times, service level. Also, the sequence in which the work–orders are produced in the production unit has to be determined. This decision is referred to as sequencing. However, when a schedule has been made, a specific sequence is implicitly defined by the schedule. The result of the scheduling function, the schedule, is transferred to the shop floor. The progress of work–orders through the shop is monitored by the scheduler.

3.3.1

Scheduling Techniques:

As a result of the research in production scheduling, a large amount of scheduling techniques, and information systems based on these techniques is available Scheduling techniques usually are based on either work–order characteristics or schedule characteristics.

3.3.1.1

Work–order characteristics

This category mainly is filled with priority dispatching rules. These rules are based on the scheduling of work–orders according to specific work–order characteristics, e.g., processing time, due–date. An example of a heuristic dispatching rule is the Shortest Processing Time (SPT) rule. If a job is completed at a work– center (i.e., a machine), the work–order with the shortest processing time will be processed next according to the SPT rule. If a heuristic is used, no schedule has to be generated in advance, and decisions about the sequence of work–orders can be made by operators at the machine level.

3.3.1.2

Schedule characteristics

Techniques that are based on schedule characteristics generate a complete schedule, usually conform some performance variable of the schedule. Some techniques find an optimal schedule by enumerating all possible schedules and choosing the best one according to a specific performance criterion, e.g., make– span. Examples of these techniques are branch and bound techniques, mathematical programming. The schedule is supposed to be (near–) optimal according to this performance variable. Bottle–neck techniques also can be found in this category. These techniques make a distinction between bottle–neck and non-– bottle–neck resources. The bottle–neck is scheduled first to ensure maximum utilization of the bottle– neck. A relatively new approach to scheduling is offered by Artificial Intelligence systems. These systems depict the

32

MSc Thesis


scheduling problem as the determination and satisfaction of a large number of hard and soft constraints.

3.4

Job Shop Scheduling

Production scheduling is both an essential and intangible factor of the logistical performance of production organizations. Much research has been carried out in production scheduling. Nevertheless, scheduling tasks can become very complex for humans, and practitioners in production scheduling often are convinced that scheduling leaves much room for improvement. In practice, formal techniques are rarely used straightforwardly, and schedulers mostly still use their own "rules–of–thumb," especially in dynamic, uncertain and complex scheduling environments, e.g., job–shops. In this report we will argue that to improve scheduling, task elements that cause task complexity should be considered for automated support. Other tasks that the scheduler performs well in comparison to techniques should preferably not be automated. To make an allocation decision, different sub- tasks within scheduling will be identified, along with the information needed to perform these tasks. This report is structured as follows: The first section gives a description of production scheduling. In the next section a brief overview of scheduling techniques will be given, along with a discussion about problems that occur when applying these techniques in practice. In the next section, the human factors relevant to scheduling will be discussed. In the following section we will present a task allocation approach for the scheduling task. Finally, conclusions are given. The implementation steps includes principles of lean applied in a unique manufacturing environment, including analysis of pre-production processes and principles of 5S, plant layout, visual controls, set up reduction, point of use storage and dynamic scheduling. Job Shop typically experience improvements including:    

50% reduced lead times 75% reduced setup times 50% increased WIP Inventory turns 20% increased capacity

3.5

Comparison of Lean and Job Shop Systems

The lean manufacturing can be compared with the job shop on the factors mentioned below;

33

MSc Thesis


Factors

Job Shop

Lean Manufacturing

Inventory

Inventory is a necessary asset. It protects against forecast errors, machine problems, and late vendors’ deliveries. More inventories are safer and necessary Keep revising the optimum lot sizes with same formulae based on the trade off between the cost of carrying inventories and the set up Low priority. Maximum output is the usual goal. Rarely does similar thought and effort go into achieving quick changeover. Use EOQ to determine lot sizes

Inventory is wasteful. It hides problems. It is a liability. Every effort must be extended to minimize the inventory

Lot Sizes

Set Ups

Vendors

Multiple sources are the rule, and it is typical to play suppliers against each other to get lower costs but multiple vendors increase the vulnerability in the components

Quality

It costs money to make high quality products. Tolerate some scrap. Track hat the actual scrap has been and develop for predicting for it As required. Not critical because inventory is available.

Equipment maintenance

Lead times

The longer the better. Most foremen and purchasing agents wish more lead times.

Workers

Engineers provide ideas and are the experts. 34

Keep reducing lot sizes. The smallest quantity is desired for both manufactured and purchased parts Eliminate/ reduce them by extremely rapid changeover to minimize the impact. Fast changeover permits small lot sizes and allows a wide variety of parts to be made frequently Produce from a single source. Vendors are remote cells, part of team. Daily multiple deliveries of active items are expected. The vendor takes care of the needs of the customer, and the customer treats the vendors as an extension of the factory. Zero defects. If quality is perfect then improvements can be made. Continuous improvements in people and process is the goal Constant and effective. Machine breakdowns and total failure are eliminated or reduced by routine maintenance Keep them short. This simplifies the job of marketing, purchasing and manufacturing as it reduces the need for expediting. The internal customers are experts. Changes are not

MSc Thesis

Cost reduction

Production control

Over head

Automation


Management is by edict. New systems are installed is spite of the workers, not thanks to the workers. Measurements are used to determine whether or not doing as directed Cost reduction comes by driving labor out of the product and by having high machine utilization

Materials should be coordinated by MRP and pushed out into the factory Over head functions are essential Automation is valued because it drives labor out of the product

made until consensus is reached. Employee involvement is critical, especially in the design of the cells. Managers are coaches who serve workers in teams Cost reduction comes by non stop like water through the pipe type manufacturing. Thus reducing the total production time Material should be pulled through the factory, using Kanban Any function that doesn’t directly add value to the product is waste. Automation is valued because it facilitates consistent quality and prevents over production

Table 2Comparison of Lean with Job Shop

3.6

Toyota Lean VS Job shop Lean

The Toyota Production System (TPS) was designed for design and operation of assembly line-type facilities. However, this type of low-variety high-volume (LVHV) manufacturing system differs significantly from the typical high-variety low-volume (HVLV) manufacturing system. Here are some specific differences between the two systems:

3.6.1 Product Variety The TPS is based on a single product family with minor variations whereas the HVLV system must be designed for a complicated material flow network resulting from the large number of dissimilar (100 to 5,000+) manufacturing routings.

3.6.2 Layout The TPS is based on the common manufacturing routing for a product family whereas the HVLV system must have a layout based on multiple dissimilar manufacturing routings.

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MSc Thesis


3.6.3 Demand Volumes The TPS relies on a high and relatively stable market demand whereas the HVLV system, being dependent on a broad customer base for business, may not have the luxury of stable demand volumes.

3.6.4 Product Design and Process Engineering The TPS can enjoy the benefits of ―variant design‖ because a car is a car is a car whereas the HVLV system often needs to design and manufacture parts and products that have little to no similarity with past orders.

3.6.5 Availability of Internal Resources The TPS is utilized by companies that often have the resources to hire full-time engineers or high-profile consulting companies to implement Lean Manufacturing. Whereas, the typical HVLV system may not have the engineering talent, technical resources and finances to finance extensive training and kaizen activities.

3.6.6 Flow line vs. Job shop Scheduling The TPS can utilize ―Takt Time‖ to schedule a single U-shaped cell based on a Single (or Mixed) Model Assembly Line Balancing problem. Whereas, the HVLV system, unless fully decomposed into independent manufacturing cells, yields a Jobshop Scheduling (JSS) problem.

3.6.7 Pull vs. Push of Orders The TPS can rely on market ―pull‖ to control inventory buffers using kanban signals. Whereas, the HVLV system, since it lacks the repetitive and stable demand, must use priority-based scheduling of orders based on their due dates and $ value.

3.7

Performance Measures

Some of the performance measures for the Lean scheduling of the job shop to be improved are discussed as under;

3.7.1 Manufacturing Lead Time: It is defined as the time of completing a product starting from raw material state to finished product state. It comprises four activities as follows;  

Operation Inspection

36

MSc Thesis

 


Transportation Delay/Storage

Only production activity is useful as it transforms the material into final shape. All other activities are nonproductive activities. The mathematical expression for manufacturing lead time is described as under; Let

To N Tno Tm

= Operation Time in a Process = No of Processes = Total Non Operation Time = Manufacturing Lead Time = nTo+ Tno

………. Equation

1

3.7.2 Work In Process It is the average number of component / Parts stored in a production system over given period of time. Work In process is considered highly significant factor in production system as large size of work in Process adversely affects production Costs. Suppose, Average monthly WIP Average Monthly Price/ Part Inventory in Pak (Rs.) IRR Opportunity Loss/ Amount Blocked in Inventory

= 100 Parts = Rs 5000 = 500000 = 2 % monthly = 1 Lac

It is evident from the example that WIP is directly dependent on manufacturing leadtime. If the lead-time is large, consequently WIP will be high, causing higher opportunity loss.

3.7.3 Productivity Improvement Productivity improvement is defined as the Ratio of output and input, where output is measured as production rate i.e. number of units produced per time and IP= Labor Hrs, M/C Hrs, Plant Hrs and other Expenditures For the same level of input, productivity can be increased if output is increased. Since output is the production rate, it implies that manufacturing lead time is inversely proportional to production rate.

3.7.4 Performance Measures relating to the Individual Job In dealing with job shop scheduling processes, it is useful to distinguish between information that is known in advance and information that is generated as a result of scheduling decisions.

37

MSc Thesis


Information that is known in advance may include the following; ai = Arrival Time of Job i. Pi = Processing Time of Job i. di= Due date of Job i. Information that is generated as a result of scheduling includes the completion time Ci. Of Job I, which is an important piece of information for evaluation of schedules vis a vis , due dates guarantees as a competitive edge to as industrial concern over others. The basic parameters are therefore; Ci =Completion Time of Job_i Mathematically, the flow time Fi is defined as ; Fi=Ci – ai

……………………………………………

Equation 2

The flow time is actually composed of; The processing Time Pi , during job I is processed by machines The waiting time Wi during which job waits in queues for other jobs to be processed Therefore Fi = Wi + Pi

………………………………………… Equation

3

Combining both Equations Fi = Ci – ai = Wi + Pi …………………………… Equation 4 Ci = ai + Wi + Pi ……………………………… Equation 5 Lateness of job has the following quantitative rlationship with the due date and completion time; Li = Ci – di

………………………………………Equation

6

Whereby, lateness Li of job i can assume +ive, 0, or – ive value depending upon whether Ci > di , Ci = di or Ci< di respectively. Therefore +ive Lateness (Tardiness) = Ti = Max (0, Li) -ive Lateness (Earliness) = Ei = Max (0,-Li)

38

MSc Thesis


The quantities defined above correspond to a specific job. However, in a Job Shop process, there is n number of jobs whereby every job takes on a specific value with regard to each of the variables defined above. In order to visualize more comprehensive information about a Schedule, these individual values are to be incorporated into some cumulative performance measures which contain information about all jobs. The cumulative performances measures include mean flow time, mean tardiness, mean lateness. These are discussed as follow;

3.7.4.1

Make span

It is total amount of time required to completely process all jobs.

3.7.4.2

Mean Flow Time

It is the average time spent by a job in the shop and comprise of processing time, waiting time and transfer time Mathematically as F= {∑ni= 1 ( F)} / n ……………………….Equation 7

3.7.4.3

Tardiness of the Job

It is the maximum value of the Lateness of the Job. It is always negative in value.

3.7.4.4

Lateness of the Job

It is defined as the difference between the completion time and the due date of the job

All the aforementioned accumulative performance measures belong to an important class of performance measures which are called regular measures of performance. A performance measure is regular if; a) It is function of the job completion times b) Its value has to be minimized c) Its value increases only if at least one of the completion times in a schedule increases The most important cumulative measure is make span M, which is the total amount required to completely process all the jobs in the shop. If all the jobs are simultaneously available (Static Environment) then the make span is the maximum flow time; M = F max = Max [ Fi ] , where i = 1,2,3, … n

It also belongs to the class of regular measures of performance.

39

MSc Thesis


4 4.1

Modeling Tools

Introduction to simulation:

Kelton el al. (1980) defines computer simulation as the methods for studying a wide variety of real world systems by numerical evaluation using software designed to imitate the system’s operation and characteristics, often overtime‖. In an increasingly competitive world, simulation came out as a puissant tool in designing, analyzing, monitoring, and scheduling of manufacturing systems. The following are some of performance measures commonly estimated by simulation.             

Throughput Time in systems for parts Time spent in queues Queue sizes Timeliness of deliveries Utilization of equipment or personnel Modeling System Randomness The following are some sources of randomness in simulated manufacturing system: Arrivals of orders, parts, or raw materials Processing, assembly, or inspection times Machine times to failure Machine repair times Loading unloading times

A simulation model is a surrogate for actually experimenting with a manufacturing system, which is often infeasible or not cost-effective. Thus, it is important for a simulation analyst to determine whether the simulation model is an accurate representation of the system being studied, i.e., whether the model is valid. It is also important for the model to be credible; otherwise, the results may never be used in the decision-making process, even if the model is ―valid.‖ The following are some important ideas/techniques for deciding the appropriate level of model detail (one of the most difficult issues when modeling a complex system), for validating a simulation model, and for developing a model with high credibility: 1. 2.

State definitively the issues to be addressed and the performance measures for evaluating a system design at the beginning of the study. Collect information on the system layout and operating procedures based on conversations with the ―expert‖ for each part of the system.

3. 4.

which becomes the major documentation for the model. Interact with the manager on a regular basis to make sure that the correct problem is being solved and to increase model credibility.

40

MSc Thesis

5.


-through (before any programming is performed) of the conceptual simulation model as embodied in the assumptions document before an audience of all key project personnel. Use sensitivity analyses [see Law and Kelton (1991)] to determine important model factors, which have to be modeled carefully. Simulate the existing manufacturing system (if there is one) and compare model performance measures (e.g., throughput and average time in system) to the comparable measures from the actual system.

6.

7.

4.1.1

Design and Analysis of simulation experiments

Because of the random nature of simulation input, a simulation run produces a statistical estimate of the true performance measures not the measure itself. 1. Length of each simulation runs 2. Number of independent simulation runs

4.2

Modeling Tool Information

Discrete event modeling techniques used are, 1. 2. 3. 4.

Analytical or mathematical technique Optimization and Expert Technique Artificial Intelligence Simulation modeling

Analytical modeling is always a useful modeling technique for simple problems. It is based on many assumptions and involves lengthy equations and mathematical calculations. But in case of this research work, problem is complicate and requires long equations and hectic calculations. It was therefore difficult to analyze the problem and this technique was not preferred for modeling. Optimization technique is based upon the concept of single goal, single system. Expert has overcome this problem but it is knowledge extensive. Artificial Intelligence is another modeling technique but not suitable for this problem. Expert is one of the cognitive science applications of AI. Expert Systems add a knowledge base and some reasoning capability to information systems. Simulation is a tool that is used in what-if scenario and gives dynamic modeling of any problem opted. A simulation is a model that mimics reality; well-known examples are flight simulators and business games. ―Simulation is the imitation of the operation of the real-world process or system over time. Simulation involves the generation of an artificial history of the system and the observation of that artificial history to draw inferences concerning the operating characteristics of the real system that is represented‖. The focus of this work is on the dynamic discrete event simulation. Discrete event simulation is used in wide range of applications, which are summarized in eight categories:

41

MSc Thesis


1. Facilities Planning: When designing a new facility, simulation is used to check that it performs correctly. 2. Obtaining the best use of current facilities: Potential solutions could be tested and identified. 3. Developing methods of control: More than just physical equipment, for example experimenting with different control logics as MRPII or Kanban etc. 4. Material Handling: Experiments can be performed to control the flow of materials to find for example bottlenecks. 5. Examining the logistics of change: To minimize interruptions simulation can be used to examine the logistics of change. 6. Company Modeling: High-level model showing for example the flows of resources and information between sites. 7. Operational Planning: Simulation can be used in day-to-day planning and scheduling 8. Training Operations Staff: Supervisors and operators are trained in the operation of the facility. Simulation benefits over real system experimentation or mathematical modeling is briefly explained in the table below. Benefits over real life experimentation Cost, Repeatability, Control over the time base, Legality and safety

Benefits over mathematical modeling Dynamic and transient effects, Non-standard distributions, interaction of random events

Managerial benefits includes Foster creative attitudes, Promotes total solutions, Makes people think, Communicating good ideas

Table 3 justification of simulation as Modeling Technique

4.2.1 Introduction Most organizations that simulate manufacturing or material-handling systems use a commercial simulation software product, rather than a general-purpose programming language (e.g., C). Furthermore, the two most common criteria for selecting simulation software are modeling flexibility (ability to model any system regardless of its complexity or uniqueness) and ease of use. A simulation language is a software package that is general in nature (in terms of the applications it can address) and where model development is done by ―programming.‖ Traditionally, programming meant the development of a simulation model by writing code, but in recent years there has been a strong movement toward simulation languages that employ a graphical model-building approach. Example of simulation languages are Arena, AweSim!, Extend, GPSS/H, Micro Saint, MODSIM III, SES/workbench, SIMPLE++, SIMSCRIPT II.5, SIMUL8, and SLX. The major advantage of a good simulation language is modeling flexibility, whereas the major disadvantage is that programming expertise is required. A manufacturing-oriented simulation language is one where the modeling constructs are specifically oriented toward manufacturing or material handling. Examples of such software are AutoMod and Quest. One advantage of this type of software is that

42

MSc Thesis


programming time may be reduced (compared to a simulation language) due to powerful constructs for such things as conveyors and AGVS. In the last five to ten years, there has been considerable interest in having simulation software that is easier to use, which largely means reducing the amount of programming required to build a model. This has given rise to what we call a manufacturing-oriented simulator, which is a simulation package designed to model a manufacturing system in a specific class of systems. This type of software has two main characteristics: 1. 2.

required to build a model (relative to simulation languages)

Arena 3.0 is a Rockwell product that is a Windows based application, used for the simulation of engineering processes. Each module has unique features and purpose of use in the simulation model. Following modules of Arena are used in upcoming model of manufacturing simulation of job shop for Lean Scheduling purpose.

4.2.1.1

Arrive

This module manages the arrival of different components into the system. The user provides the time between arrival and the batch size for each component.

4.2.1.2

Depart

This module manages the departure of different components from the system. Information required is type of statistics to be maintained and type of counter provided.

4.2.1.3

Server

This module is analogous for any machine that can process any component. This module requires the input process time and capacity or schedule.

4.2.1.4

Sequence

The sequence module, found on the common panel, allows defining a sequence of station visitations consisting of a list of destination stations and optional assignments of attributes or variables at each station.

4.2.1.5

Set

Arena Sets are groups of similar objects that can be referred by a common name (the set name) or a set index. The objects that make up the sets are referred to as member of the set. Member of a particular set must always be the same type of objects, such as resources, queues, pictures, others, etc.

43

MSc Thesis


4.2.1.6

Variables

This module allows defining global variables and their initial values. The variables then can be referenced in the model by their names.

4.2.1.7

Expressions

This module allows defining expressions and their associated values.

4.2.1.8

Statistics

This module specifies additional statistics to be collected, as well as specifying which data we would like to save to files.

4.2.1.9

Resource

This module allows defining different resource characteristics.

4.2.1.10

Transporter

This module allows defining the transporters used in the manufacturing set up.

4.2.1.11

Conveyor

This module, found in the transfer panel, allows defining the conveyors between the stations.

4.3

The primary Template – Arena

The Arena template is the core collection of more than 60 modules provided as part of the general Arena System. It is designed to provide a general-purpose collection of modeling features for all types of applications. In addition to providing core features for resources, queuing, inspection, system logic and external file interfaces, the Arena template provides modules specifically focused on specific aspects of manufacturing and material handling. For manufacturing, it contains modules that incorporate such features as machine downtime and maintenance schedules. For material handling applications, modules exist for representing conveyors (accumulating and non-accumulating) and various types of transportation devices. Three panels compose the Arena template: the common panel, the support panel, the transfer panel. Modules from these panels can be combined in the same model. In order to develop a simulation model using the Arena template, the user simply picks a module, places it in the model, and then is prompted for the necessary information. For example, when placing the Server module from the Arena template, the user is asked for

44

MSc Thesis


such information as how long entities spend at the server, the server’s operating schedule, and where entities should go. After responding with the appropriate information, the user closes the dialogue to accept the completed module. Animation is automatically included with many of the modules in the Arena template to allow for rapid development of simulation model. Graphics symbols are provided when placing a module from the Arena Template can be changed with Arena’s built in graphics tools or can be replaced with icons from Arena’s Symbol library or from external applications.

4.3.1 Animation: Arena animations can be run either concurrently with the executing simulation model or in post process mode. Animations can be created in several ways: can be created entirely using Arena’s graphics drawing tools; can be created from Auto CAD or other. Arena’s drawing tools include all standard CAD objects and provide virtually unlimited color selection. Arena includes various animation options for real time display of model statistics. For example, the user can place dynamic plots, histograms, levels, and time clocks directly within a simulation in order to illustrate system status as the model performs. This information is displayed on a real time basis as well as on a post process basis in the Arena statistical summary report.

4.3.2 Input/output Analyzers Arena contains additional tools that are variable for conducting entire simulation projects. The input analyzer is used for the determining an appropriate distribution for input to an Arena Model. The input analyzer allows the user to take raw data (e.g. time studies on process breakdowns or historically based order level information) and fit it to a statistical distribution. The output analyzer is used to display and analyze model data after the simulation run (or runs) has been completed. Graphical display options include plots, histograms and more. Multiple replications can be displayed on a single chart or can be lumped together for display of the aggregate performance over multiple runs. The output analyzer also provides analysis features such as confidence intervals, one way analysis of variances, and comparisons of multiple systems. Both the input and output analyzers are directly available on the Arena Tools menu.

45

MSc Thesis


5 5.1

Analysis and methodology of Research

Applied methodology

In this research, many techniques have been applied to build a lean cell. As first step a current state value stream map is drawn to identify the wastes or non-value added activities. After this a future state value stream map is proposed. Then the next step was to form a GT cell for the job shop activities selected. The first step was to arrange the machinery in a sequence. The next was to optimize the cell in such a way that all the parameters of a Lean manufacturing were met. The first step towards lean parameters was to achieve high utilization of the available resources, then to reduce the cycle times and Work in Process but at the same time throughput of the system was optimized. The cell is then linked to the final assembly line through Kanban system. The appendices consist of table and figures to justify the research methodology including GT Cell formation and Time Study carried out.

Table 4 Lean methodology

5.2

Flexibility in cell design

The key function design requirement for a manufacturing or assembly cell is flexibility. Manufacturing cells should not be confused with flexible manufacturing system. Cells are operationally different. Manufacturing cells have several types of flexibility, where as, 46

MSc Thesis


flexible manufacturing cells have little real flexibility. Manufacturing flexibility considers;  Adaptability to change of product design  Ability to reconfigure a manufacturing system or sub system easily  And ability to adapt to product mix and volume change First to be flexible, the process or manufacturing sub system must be able to handle all product design changes. Engineering design changes are routine facts of life. This applies equally to new product designs. The later is called concurrent design and reflects the ability to a company to bring new products to the market quickly. Second, to be flexible, the manufacturing system must be able to reconfigure, that is , redesign, easily. The design should not be viewed as fixed and unchangeable, as is often the case in the job or flow shop. Design of a manufacturing system dictates material flow, and this must be done efficiently. Third is to be flexible, an existing manufacturing system should be able to changes in the product mix, as well as existing volume, or changes in customer demand for he product. Flexibility is also built in when a process and its applicable tooling are adaptable to many types of products. It requires rapid changeover of jigs, fixtures and tooling for existing products and rapid modification for new designs. The process has excess capacity. This means that they can run faster if needed, but are designed for operating at less than full capacity.

5.3

Lean manufacturing cells

Lean manufacturing cells are different from the interim manufacturing cells described in interim cells, designed with machines tools used in a job shop, are the predictors for the lean cells. In a true lean manufacturing system, manufacturing equipment must be designed, built and tested and implemented into manufacturing cells. This includes machine tools and processes, tooling such as work holders, cutting tools, and material handling devices, especially de couplers. Simple, reliable equipment that can be easily maintained should be specified. In general, flexible, dedicated equipment that can be built in house is better than if it is purchased and modified for the needs of a cell. Many companies understand that it is good strategy to simply imitate or copy manufacturing process technology from another company, and then to expect to make an exceptional product using the same technology that a competitor uses. When process technology is purchased from outside vendors, unique aspects are quickly lost. The lean company must carry out research and development on manufacturing technologies as well as manufacturing systems to produce competitive and cost efficient products. Effective, cost efficient manufacturing is the result of research and development in manufacturing process technology.

47

MSc Thesis

5.4


Case Study -01

The first case study includes the Hull Repair Section of the HIT which is responsible to rebuild the parts of suspension and power pack to the OEM standards. The facility lay out is shown in the figure. The performance of the Lean Set up against the existing set up can be measured on the basis of the following factors; 1. Work In Process (WIP) 2. Over/ Under Production 3. Average Cycle Times 4. Throughput 5. Quality 6. Transportation 7. Job Satisfaction 8. Cost Reduction 9. Work place Area 10. Delivery / Target (Mean Tardiness)

5.4.1

Work in Process Inventory (WIP):

Work in Process inventory is another factor that determines the performance of any Lay Out. Lower the WIP, the more efficient the lay out will be. Figure 3 is graphical representation of the WIP inventory in the existing as well as the Lean Cell. It is clear that the Lean Cells have considerably reduced the WIP and are reducing the cost of the WIP inventory as compared to the existing set up. The most economical WIP inventory is for the Lean Cell with Loop Conveyors. WIP 25

WIP

20 15 WIP

10 5 0

WIP

Lean Cell With Loop Conveyor

Lean Cell with Manual Handling

8.5085

10

Lean Cell With Transporters

System

11.323

Figure 2Comparison of WIP

48

Existing Manufacturing Set Up 22.85

MSc Thesis

5.4.2


Average Cycle Times:

Cycle Times or flow times are most important factor to compare a type of Lay Out with another. Cycle Time or Flow Time is Total Time required to completely rebuild a part is termed as Cycle Time. A comparison of the existing with the Lean Cells is presented in the table 5 below;

Parts Description Balance Arm Crank Arm Driven Gear Driven Shaft Sprocket Hub Final Drive Cover Worm Idler Wheel Disk Shock Absorber Blade Left Right Supports

Lean Cell With Transporters 196.17 103.31 187.83 410.76 708.48 419.01 192.05 455.29

Lean cell With Manual Handling 193.24 95.751 178.65 284.89 751.11 294.47 181.81 271.11

183.42 272.2

160.76 282.39

Lean Cell With Conveyor 186.42 94.276 169.4 289.96 522.11 272.01 187.25 276.82

Existing Set Up 1034.8 1115 1507.7 1358.3 757.7 328.57 1785.4 377.91

163.42 272.2

1065 1950.9

Table 5 Comparison of Average Cycle Times

The below mentioned graph clearly depicts that Lean Cells have reduced the total Cycle Times considerably. Lean Cells Vs Existing Set Up

2000


1500

Lean cell With Manual Handling Lean Cell With Conveyor

1000

Existing Set Up 500

Shock Absorber

Worm Cycle

Sprocket Hub

Driven Gear

0

Balance Arm

Avg Cycle Times

2500

Part Family

Figure 3Lean Cells Vs Existing Set Up

49

MSc Thesis


Manual Lean Cell has an edge over the Lean Cell with Transporters. The reason is that Loading and unloading times are not included in the Manual Lean Cell.

5.4.3

Tardiness of the Scheduling

The tardiness of the job is another factor that determines the performance of a Lay Out and if it is improved it is possible to meet the targets well in advance. The Tardiness can be calculated for all the cases and is explained as under; 5.4.3.1 Tardiness of the Jobs in Existing Set Up: The table shows that the jobs in the existing set up are not well scheduled and have tardiness in almost all the jobs, which depicts that it will be impossible to meet the targets in the present scenario.

Balance Arm Crank Arm Driven Gear Driven Shaft Sprocket Hub Final Drive Cover Worm Idler Wheel Disk Shock Absorber Blade Left Right Supports

Existing Set Up

Monthly Target

1034.8 1115 1507.7 1358.3 757.7 328.57 1785.4 377.91

100 20 20 20 20 20 20 20

1065 1950.9

40 20

Monthly Time Available

12120

Parts Description

Completion Time

Difference

103480 22300 30154 27166 15154 6571.4 35708 7558.2

-91360 -10180 -18034 -15046 -3034 5548.6 -23588 4561.8

42600 39018

-30480 -26898

Earliness

-91360 -10180 -18034 -15046 -3034 5548.6

Table 6 Tardiness of the Jobs in Existing Set Up

5.4.3.2 Tardiness of the Jobs in Lean Cell with Loop Conveyors: The table shows that almost all the parts are being rebuilt well in advance except one part that has tardiness and it can be controlled as well

50

Tardiness

-23588 4561.8 -30480 -26898

Parts Description


Lean Cell With Conveyor

Monthly Target

186.42 94.276 169.4 289.96 522.11 272.01 187.25 276.82

100 20 20 20 20 20 20 20

163.42 272.2

40 20



Completion Time

Difference

Earliness

18642 1885.52 3388 5799.2 10442.2 5440.2 3745 5536.4

-6522 10234.48 8732 6320.8 1677.8 6679.8 8375 6583.6

10234.48 8732 6320.8 1677.8 6679.8 8375 6583.6

6536.8 5444

5583.2 6676

5583.2 6676

12120

MSc Thesis

Tardiness

-6522

Table 7 Tardiness of Job in Lean Cell with Loop Conveyors

The figure below depicts that the parts are produced well in advance than the due dates and it is possible to reduce the over times to cut the expenses. 20000

Time

18000 16000 14000 12000

Mothly Time Available

10000 8000

Lean Cell With Loop Conveyor

6000 4000

B

al an ce

A C rm ra nk D Arm ri ve n D Ge ri ve ar n S S ha pr o ck ft F in et al H u D riv b e C ov er Id l W e S ho r W or ck he m e A bs l D o Le rb isk e ft R rB ig l ht ad S e up po rt s

2000 0

Parts Family

Figure 4Tardiness in Lean Cell with Loop Conveyors

5.4.3.3 Tardiness of the Jobs in Lean Cell with Transporters: The table shows that the Cell is efficient but less as compared to the Loop Conveyor Lean Cell. Sprocket Hubs are not being produced well in time and it will be a little tough to control the situation.

51

MSc Thesis



183.42 272.2

Monthly Target

100 20 20 20 20 20 20 20


12120

Lean Cell With Transporters 196.17 103.31 187.83 410.76 708.48 419.01 192.05 455.29

Parts Description

40 20

Completion Time

Difference

19617 2066.2 3756.6 8215.2 14169.6 8380.2 3841 9105.8

-7497 10053.8 8363.4 3904.8 -2049.6 3739.8 8279 3014.2

7336.8 5444

4783.2 6676

Earliness

Tardiness

-7497 10053.8 8363.4 3904.8 -2049.6 3739.8 8279 3014.2 4783.2 6676

Table 8 Tardiness of jobs in Lean Cells with Transporters

The Figure shows that the cell has the tendency to meet the targets but lack in the case of the balance arms and the Sprocket Hubs 25000

Time

20000 Mothly Time Available

15000


10000 5000

B

al an ce

C Arm ra nk D A ri rm ve n D G ri ea ve r S nS pr h F oc af in k e t al t D Hu riv b e C ov Id er S le W ho r ck W o r h m A ee bs l D Le or i ft be sk R r B ig ht lad S e up po rt s

0

Parts Family

Figure 5Tardiness in Lean Cell with Transporters

5.4.3.4 Tardiness of the Jobs in Lean Cell with Manual Handling: The Lean Cell with the Manual Handling has almost the same status as that of the Lean Cell with Transporters.

52


Lean cell With Manual Handling

Parts Description


193.24 95.751 178.65 284.89 751.11 294.47 181.81 271.11 160.76 282.39

Monthly Target

100 20 20 20 20 20 20 20 40 20


Completion Time

Difference

12120

MSc Thesis

19324 1915.02 3573 5697.8 15022.2 5889.4 3636.2 5422.2 6430.4 5647.8

-7204 10204.98 8547 6422.2 -2902.2 6230.6 8483.8 6697.8 5689.6 6472.2

Earliness

Tardiness

-7204 10204.98 8547 6422.2 -2902.2 6230.6 8483.8 6697.8 5689.6 6472.2

Table 9 Tardiness in Lean Cell with Manual Handling

The figure shows that the targets are being met to some extent the need is to control the times of the Sprocket Hubs and the Balance Arms. 25000

Time

20000 15000

Mothly Time Available

10000

Lean Cell With Manual Handling

5000

B

al an ce

Ar C ra m nk A D riv rm en G D r iv e a en r S pr Sh o c af Fi ke t na t l D Hu b riv e C ov er Id le W S rW ho or ck he m A bs el D is Le o rb er k ft R ig B la ht de S up po rts

0

Parts Family

Figure 6 Tardiness in Lean Cell with Manual Handling

5.4.4

Utilization of the Resources:

The Utilization of the resources in another factor needs to be optimized in Lean Scheduling of the parts. The following analysis of the results shows this performance measure in detail. 5.4.4.1 Utilization of the Resources in Existing Set Up: The table shows the utilization of the resources in the existing set up.

53

MSc Thesis

Lean Scheduling in High Variety, Low Volume Environment Utilization in Existing Set Up 0.9541 0.51899 0.39393 0.44314 1.6483 0.38343 0.56505 0.45542 0.22717 0.53026

Machine Tools Center Lathe Radial Drilling Machine Universal Cylindrical Grinder Broaching Machine Gear Lathe Vertical Lathe Vertical Mill Universal Mill Bench Drilling Machine Inspection Cum Bench Fitting

Resource Available 1 1 1 1 2 1 1 1 1 1

Table 10 Resource Utilization in Existing Set Up

The figure clearly shows that most of the resources are either under utilized or over utilized and the performance measure needs to be optimized. Utilization in Existing Set Up 1.8 1.6

Utilization

1.4 1.2 1

Utilization in Existing Set Up

0.8 0.6 0.4 0.2

Bench Drilling

Vertical Mill

Gear Lathe

Universal Cylindrical

Center Lathe

0

Parts

Figure 7Utilization of the Resources in the Existing Set Up

5.4.4.2 Utilization of the Resources in Manual Handling: The Table for the Manual Lean Cell shows that almost all the resources are well utilized except CNC Horizontal Boring Machine. The ideal utilization of the resources in Lean Cell is about 95 per cent but never more than it. Machine Tools

Utilization in lean Cell With Manual Handling

Resource Available

CNC Lathe

1.9385

3

CNC Horizontal Boring Machine

1.169

1

Universal Cylindrical Grinder

0.84251

1

Broaching Machine

0.58149

1

Inspection Cum Bench Fitting

1.0997

2

Table 11Resource Utilization in Lean with Manual Handling

54

MSc Thesis


The figure below shows the detail of the resource utilization and it shows that universal Cylindrical Grinder is ideally utilized. Utilzation in lean Cell With Manual Handling

1.0997 1.9385 CNC Lathe CNC Horizontal Boring Machine 0.58149

Universal Cylindrical Grinder Broaching Machine Inspection Cum Bench Fitting

0.84251 1.169

Figure 8 Utilization in Lean Cell with Manual Handling

5.4.4.3 Utilization of the Resources in Lean Cell with Transporters: The situation of the utilization of the resources in this case is almost the same as that of the Lean Cell with Manual Handling. There are many resources that need to be optimized.

Machine Tools

Utilization in lean Cell With Transporters

Resource Available

CNC Lathe

1.9385

3


1.169

1


0.84251

1

Broaching Machine

0.58149

1


1.0997

2

Table 12Resource Utilization in Lean Cell

The Figure below shows that CNC Horizontal Boring Machine and Broaching machine are not scheduled for optimal utilization. .

55

MSc Thesis


Utilzation in lean Cell With Transporters

1.0997 1.9385 CNC Lathe CNC Horizontal Boring Machine 0.58149

Universal Cylindrical Grinder Broaching Machine Inspection Cum Bench Fitting

0.84251 1.169

Figure 9 Utilization in Lean Cell with Transporters II

5.4.4.4 Utilization of the Resources in Lean Cell with Loop Conveyors: The table for the Lean Cell with the Loop Conveyors shows that the all the resources are well optimized. Utilization in lean Cell With Loop Conveyor

Machine Tools

Resource Available

CNC Lathe

1.7136

3


0.90342

1


0.56665

1

Broaching Machine

0.69382

1


1.1099

2

Table 13 Resource Utilization in Lean Cell with Loop Conveyors

It has already been discussed that ideal utilization of the resources should reach 90 per cent in Lean Cell but it should never be above 95 per cent. The below mentioned graph depicts this situation.

56

MSc Thesis


3.5 Utilization 3 2.5

Utilzation in lean Cell With Loop Conveyor

2

Resource Available

1.5 1 0.5 0 CNC Lathe

Broaching Machine Universal Cylindrical Grinder Inspection Cum Bench Fitting CNC Horizontal Boring Machine

Figure 10 Utilization Vs Resources Available

5.4.5

Under Production / Over Production:

Under production is the factor to determine whether the Lay Out opted has the desired effect in meeting the target. This performance measure has important place in Lean Manufacturing. 5.4.5.1

Under Production in Existing Set Up:

The Table shows that existing set up is unable to meet the targets set for the monthly production. Almost all the parts are facing under production.

Figure 13.30 shows that the existing set up is even unable to produce 10 per cent of the targeted quantity. The other part facing deficit is Shock absorber Blade. Under Production in Existing System

14 Balance Arm 29

Crank Arm Driven Gear Driven Shaft 88

12

Sprocket Hub Final Drive Cover Worm

13

Idler Wheel Disk Shock Absorber Blade

4

Left Right Supports

11 12

9

57

MSc Thesis

Lean Scheduling in High Variety, Low Volume Environment Figure 11 Under Production in Existing Set Up

5.4.5.2

Under Production in Lean Cell with Loop Conveyors:

Lean Cell is efficient enough to meet the targeted quantities of almost all the parts. Figure shows that only the balance arms are facing under production and the quantity can be increased if the processing times are further through Quick Change over Techniques. 5.4.5.3

Under Production in Lean Cell with Manual Handling:

The figures below is graphical representation of the Lean Cell with Manual Handling Case.

Under Production in Manual Lean

4 Balance Arm Crank Arm Driven Gear Driven Shaft Sprocket Hub Final Drive Cover Worm Idler Wheel Disk Shock Absorber Blade Left Right Supports 38

Figure 12 Under Production in Lean Cell with Manual Handling

5.4.5.4

Under Production in Lean Cell with Transporters:

The table below shows that the case is under producing the Balance Arms and the Sprocket Hubs and a careful study can further improve the situation through reduction of the Queue times.

58

MSc Thesis


Under Production in Lean with Transporters

3 Balance Arm Crank Arm Driven Gear Driven Shaft Sprocket Hub Final Drive Cover Worm Idler Wheel Disk Shock Absorber Blade Left Right Supports 38

Figure 13 Under Production in Lean Cell with Transporters

5.4.6 Production Volumes Throughput is another factor to determine the performance of the manufacturing Lay Outs. More throughput shows that the lay out is more economical and efficient. In my research I have taken it as an important factor to be optimized. The table below shows that the throughput is improved in the Lean Cells if compared with the existing set up. Parts Description


% Completion ( Existing System)

% Completion (Lean With conveyors)

% Completion (Lean With Transporters)

% Completion ( Manual Handling Lean)

12 55 40 45 80 100 35 40 27.5 30

66 100 100 100 100 100 100 100 100 100

62 100 100 100 80 100 100 100 100 100

62 100 100 100 85 100 100 100 100 100

Table 14 Comparison of Throughput

5.4.6.1 Throughput in Existing Set Up:

The figure below shows that the existing set up is in efficient to produce the targeted parts. The throughput is quite below the targeted value.

59

Throuhput

MSc Thesis


120 100 80 60 40 20 0

% Completion Target Line

Figure 14 Throughput in Existing Set Up

5.4.6.2 Throughput in Lean Cell with Loop Conveyors:

Throughput

Figure shows that throughput is almost within the range for the targeted value except for one part. 120 100 80 60 40 20 0

% Completion (Lean With conveyors) Target Line

Throughput in Lean Cell with Loop conveyors

5.4.6.3 Throughput in Lean Cell with Transporters: The lean cell with Transporters lags in the production of two parts. Hence the lay out must be optimized.

60

Throughput

MSc Thesis


120 100 80 60 40 20 0

% Completion (Lean With Transporters) Target Line

Figure 15Throughput in Lean Cell with Transporters

5.4.6.4 Throughput in Lean Cell with Manual Handling:

Throughput

The Lean Cell with manual handling has almost the same situation as that of the Lean ell with Transporters. 120 100 80 60 40 20 0

% Completion ( Manual Hanling Lean) Target Line

Figure 16 Throughput in Lean Cell with Manual Handling

61

MSc Thesis

5.5


Cost analysis of manufacturing Lay Outs:

Manufacturing cost can be categorized into two major categories: 1) Fixed Costs 2) Variable Costs A fixed cost is one that remains constant for any level of production output Examples include the cost of the factory building and production equipment, insurance and property taxes. A variable cost is one that varies in production to the level of production output. Examples include direct labor, raw material, and electric power to operate the production equipment. The total cost equation is as under;

5.5.1

TC =FC + VC (Q) Existing System

The Cost calculation for the existing set up in the categories of the fixed cost and the variable cost are as under; 5.5.1.1

Fixed Cost

Fixed cost calculation for the existing set up is as under; Machine Tool Center Lathe Gear Lathe Vertical Lathe Universal Mill Vertical Mill Universal Cylindrical Grinder Radial Drilling Machine Drilling Machine Broaching Machine Bench Fitting Fixed Price

Unit Price 87000 123000 156000 90000 87000 230000 123000 65000 270000 50000

Total Price 174000 246000 156000 90000 87000 230000 123000 65000 270000 50000 1491000

Table 15 Fixed Cost for Existing Set Up

UAC

= 1491000{(1 + 0.25)10 x 0.25} / {(1+0.25) 10 -1} = Rs. 418054.2

5.5.1.2

Variable Cost:

It comprises of all the costs that vary with the production. 62

MSc Thesis


5.5.1.2.1

Labor Cost:

No of workers = 14 Monthly Salary of the workers = 3 x 3785 +1 x 9873.25 + 4 x 5350 + 3 x 7213 + 1x 8218 = 72 479.5 No of Hrs (Monthly) = 202 Hourly rate of labor = 72479.5/ 202 = 358.809 Rs. / hr No. of units Produced = 108 / Month = 0.534 units / hr Labor Cost Per Part = 358.809 / 0.534 = Rs. 671.94 5.5.1.2.2

Cost of Electricity:

This cost can be calculated by taking the wattage power of all the machines and then using the rate of power per KWH. Machine Tool Center Lathe Gear Lathe Vertical Lathe Universal Mill Vertical Mill Universal Cylindrical Grinder Radial Drilling Machine Drilling Machine Broaching Machine Bench Fitting

Motor Hp 11 KW 11 KW 22 KW 7.5 KW 11 KW 15 KW 5.5 KW 5.5 KW 22 KW Nil

Table 16 Power Requirements for Existing Set Up

Total Electric Power Requirements = 110.5 KW Commercial Rate of Electric Power = Rs. 3.5 /KWH Cost of Electric Power = 110.5 / 3.5 = Rs. 31.6 per Hr

5.5.1.2.3

Tooling Cost:

Total Tooling expenses per Month Hourly Tooling Charges

= Rs. 3500 = 3500 / 202 = Rs. 17.33

Tooling Cost per Part

= 17.33 / 0.534 = Rs. 32.5

63

MSc Thesis


5.5.1.2.4

Raw Material Cost:

All the Parts are to be rebuilt; hence the cost of raw material is zero.

Variable Cost

= Labor Cost+ Tooling Cost + Electricity Cost =32.5+31.6+671.94 = Rs. 736 5.5.1.2.5 TC

5.5.2

Total Cost:

= FC + VC (x) = 418054.2 + 736 (300) = Rs. 638854.2

Lean Lay Out

The cost analysis for the Lean Cell is made assuming that the salvage cost of the equipment is zero and the rate of return is 25% 5.5.2.1

Fixed Cost:

The fixed Cost calculations for the Lean Cell are as under; Machine Tool CNC Lathe CNC Horizontal Boring Machine Universal Cylindrical Grinder Cost of Conveyors Radial Drilling Machine Broaching Machine Total Equipment Cost

Unit Price 600000 1100000

Total Price 1800000 1100000

230000 100000 123000 270000

230000 100000 123000 270000 4523000

Table 17 Fixed Cost for Lean Cell

UAC

= 4523000{(1 + 0.25)10 x 0.25} / {(1+0.25) 10 -1} =Rs. 1239178.2

5.5.2.2

Variable Cost:

The variable cost calculation for the Lean Cell is under;

64

MSc Thesis


5.5.2.2.1

Labor Cost:

No of workers Monthly Salary of the workers No of Hrs (Monthly) Hourly rate of labor No. of units Produced Labor Cost Per Part 5.5.2.2.2

=2 = 2 x 6718 = 13436 = 202 = 13436/ 202 =Rs. 66.51 Hr = 266 / Month = 1.32 units / hr = 66.51 / 1.32 = Rs. 50.4

Electricity Cost:

Machine Tool

Motor Power 8 KW 12 KW 15 KW 5.5 KW 22 KW

CNC Lathe CNC Horizontal Boring Machine Universal Cylindrical Grinder Radial Drilling Machine Broaching Machine

Table 18 Power Requirement for Lean Cell

Total Electric Power Requirement = 62.5 KW Commercial Rate of Electric Power = Rs 3.5 per KWH Hourly Electric Charges = 62.5 / 3.5 = Rs.17.86 5.5.2.2.3

Tooling Cost:

Total Tooling expenses per Month Hourly Tooling Charges

= Rs. 15000 = 15000 / 202 = Rs. 74.25

Tooling Cost per Part

= 74.25/ 1.32 = Rs. 56.25

5.5.2.2.4

Raw Material Cost:

All the Parts are to be rebuilt; hence the cost of raw material is zero.

Variable Cost

= Labor Cost+ Tooling Cost + Electricity Cost =56.25+17.86 + 50.4 = Rs. 124.5

65

MSc Thesis


5.5.2.2.5

Total Cost:

Total cost for the Lean Cell is; TC

= FC + VC (x) = 1239178.2+ 124.5(300) = Rs. 1493236.2

5.4.7

Cost Reduction

Another factor that improves the performance through economical optimization is Cost reduction. The table shows the comparison of the costs for 0, 300, 1000, 2000, 3000, and 4000 parts per month. The figure shows that the Lean Cell becomes economical after the production of about 2000 parts. It is also clear that the monthly production of the parts is 300 and 2000 parts will be produced. The requirement for a Lean Cell is the reduction of cost as well as the Floor Space area. These parameters are also improved for the Lean Cells.

4000000 3500000 3000000 2500000

Quantity

2000000

Existing Set Up

1500000

Lean Set Up

1000000 500000 0 Quantity

1

2

3

4

5

6

0

300

1000

2000

3000

4000

Existing Set Up

418055 638854 1154054 1890054 2626054 3362054

Lean Set Up

1239178 1276528 1363678 1488178 1612678 1737178

Figure 17 Break Even Analysis

5.4.8

Work Place Area

Another factor to improve the performance of the manufacturing lay out is the reduction of the floor space area and the current and theoretical lay out of the Lean Cells suggests that the floor space has reduced 03 times.

66

MSc Thesis


Floor Space 3.5 3

Area

2.5 2

Floor Space

1.5 1 0.5 0 Existing Set Up

Lean Cell

Figure 18 Work Place Area

5.4.9

Conclusion

The performance measures selected to compare the lean cell with existing set up have been improved. If we look at tardiness, it is reduced in case of the lean cells. Introducing automated material handling has also shown positive impacts on the production. Timely delivery of the parts has also been assured, with reduced processing time. Resources are being well utilized. The situation of starvation and saturation has been addressed to a greater extent. It is quite evident that lean is a better option for the problem addressed.

67

MSc Thesis

5.6


Case Study – 02

The second case study is about the manufacturing set up of the HIT. The shop chosen is responsible to manufacture the tooling for the entire factory. There is a large variety of the parts that are manufactured in the factory but the volume of these parts is quite low. DESCOM is a supporting facility of HIT and has been specifically structured to take up this very vital task and its activities include the in-house manufacture of components and assemblies, designing and manufacturing of tools and gauges, repair and maintenance of machinery and services installed in factories and the development and subsequent production of components and assemblies through vendor industries. DESCOM has three major shops 1) Components Manufacturing Shop 2) Tooling Shop 3) Maintenance and Services. Focus of this study is the Tooling Shop. The Shop is manufacturing all kinds of tooling and gauges for the production units of HIT.

5.6.1

GT Cell Formation:

The first step was to make the part families with similar shape or processing characteristics. 1. 2. 3. 4.

Cutter Part Family Reamer & Drill Part Family Gears Part Family Lathe Tools Part Family

5.6.2

Scope of the Case Study:

The scope of the case study is to compare following Performance measures 1. 2. 3. 4. 5.

Mean WIP Level Mean Flow Time Mean Queue Times Production Volumes Mean Tardiness

5.6.2.1

Weeks Vs WIP Level

The combined WIP is compared with the existing tool Room and the results show that Lean Cells have reduced the WIP inventory considerably. WIP in individual cases is also shown for better understanding of the Lean Cells.

68

MSc Thesis


18 16

Mean WIP In Lean Cell 1

14

WIP

12

Mean WIP In Lean Cell 2

10 8

Mean WIP In Lean Cells

6 4

Mean WIP In Existing Tool Room

2 0 1

3

5

7

9

11 13 15 17 19 21 23 25 27 Weeks

Figure 19Comparison of Mean WIP

5.6.2.2

Weeks Vs Mean Flow Times

Mean Flow Times for the Corn Cutter in Existing Tool Room and Lean Cell are compared. The results show that Lean Cell has lesser Flow Times than the Existing Tool Room.

Mean Flow Times

Corn Mill Cutter Flow Time

2500 2000 1500 1000 500 0 1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Weeks

Existing Tool Room

Lean Cell

Figure 20 Mean Flow Time Comparison I

69

MSc Thesis


Mean Flow Times for Side and Face Mill Cutter in Existing Tool Room and Lean Cell are compared. The results show that Lean Cell has lesser Flow Times than the Existing Tool Room.

Mean Flow Times

Side and Face Mill Cutter

2000 1800 1600 1400 1200 1000 800 600 400 200 0 1

3

5

7

9

11

13

15

17

19

21

23

25

27

Weeks

Existing Tool Room

Lean Cell

Figure 21Mean Flow Times Comparison II

Mean Flow Times for the Module Cutter in Existing Tool Room and Lean Cell are compared. The results show that Lean Cell has lesser Flow Times than the Existing Tool Room.

Mean Flow Times

Module Cutter

2500 2000 1500 1000 500 0 1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Weeks

Existing Tool Room

Lean Cell

Figure 22 Mean Flow Time Comparison III

70

MSc Thesis


Mean Flow Times for the End Mill Cutter in Existing Tool Room and Lean Cell are compared. The results show that Lean Cell has lesser Flow Times than the Existing Tool Room.

Mean Flow Times

End Mill Cutter

2000 1800 1600 1400 1200 1000 800 600 400 200 0 1

3

5

7

9

11

13

15

17

19

21

23

25

27

Weeks

Existing Tool Room

Lean Cell

Figure 23 Mean Flow Time Comparison IV

Mean Flow Times for the Reamers in Existing Tool Room and Lean Cell are compared. The results show that Lean Cell has more Flow Times than the Existing Tool Room. The reason is that Existing Tool Room has two options either to follow route for Universal Mill or the Horizontal Mill. This option reduces the Flow Times in the case of Existing Tool Room.

Mean Flow Times

Reamer

900 800 700 600 500 400 300 200 100 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Weeks

Existing Tool Room

Lean Cell

Figure 24 Mean Flow Time Comparison V

71

MSc Thesis


Mean Flow Times for the Drills in Existing Tool Room and Lean Cell are compared. The results show that Lean Cell has lesser Flow Times than the Existing Tool Room.

Mean Flow Times

Drills 1200 1000 800 600 400 200 0 1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Weeks Existing Tool Room

Lean Cell

Figure 25 Mean Flow Times Comparison VI

Mean Flow Times for the Shafts and Fixtures in Existing Tool Room and Lean Cell are compared. The results show that Lean Cell has more Flow Times than the Existing Tool Room. The reason is that Existing Tool Room has two options either to follow route for Universal Mill or the Horizontal Mill. This option reduces the Flow Times in the case of Existing Tool Room.

Mean Flow Times

Various Shafts and Fixtures

900 800 700 600 500 400 300 200 100 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 Weeks

Existing Tool Room

Lean Cell

Figure 26 Mean Flow Times Comparison VII

72

MSc Thesis


Mean Flow Times for the Corn Cutter in Existing Tool Room and Lean Cell are compared. The results show that Lean Cell has lesser Flow Times than the Existing Tool Room.

MEan Flow Times

Gears and Gear Shafts 1600 1400 1200 1000 800 600 400 200 0 1

3

5

7

9

11

13

15

17

19

21

23

25

27

Weeks Existing Tool Room

Lean Cell

Figure 27 Mean Flow Times Comparison VIII

5.6.2.3

Weeks Vs Production Volumes

Production Volumes is another measure to compare the types of Lay Outs. The figure shows that the Corn Mill Cutter has more Production Volumes in the case of Lean Type production than the Existing Tool Room which is Process Type Lay Out.

Production Volume

Corn Mill Cutter

4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 1

3

5

7

9

11

13

15

17

19

21

23

25

Weeks

Existing

Lean Cell

Figure 28 Production Volumes I

Side and Face Mill Cutter are produced in Lean Cell in more quantity than that of Existing Set Up.

73

27

MSc Thesis


Production Volumes

Side And Face Mill Cutter

5 4.5 4 3.5 3 2.5 2 1.5 1 0.5 0 1

3

5

7

9

11

13

15

17

19

21

23

25

27

Weeks

Existing

Lean Cell

Figure 29 Production Volumes II

Module Cutters are produced in Lean Cell in more quantity than that of Existing Set Up. In the case of Existing Tool Room, there are some instances when there is zero production of Module cutters.

Production volumes

Module Cutter

6 5 4 3 2 1 0 1

3

5

7

9

11

13

15

17

19

21

23

25

27

Weeks

Existing

Lean Cell

Figure 30 Production Volumes III

End Mill Cutters are produced in Lean Cell in more quantity than that of Existing Set Up.

74

MSc Thesis


Production Volumes

End Mill Cutter

6 5 4 3 2 1 0 1

3

5

7

9

11

13

15

17

19

21

23

25

27

Weeks

Existing

Lean Cell

Figure 31 Production Volume IV

Reamers are produced in more quantity mainly due to lesser work load on the universal mill due to another route for the gears and drills.

Prodcution Volumes

Reamers

8 7 6 5 4 3 2 1 0 1

3

5

7

9

11

13

15

17

19

21

23

Weeks

Existing

Lean Cell

Figure 32 Production Volume V

Drills are produced in Lean Cell in more quantity than that of Existing Set Up.

75

25

27

MSc Thesis


Production Volumes

Drills

9 8 7 6 5 4 3 2 1 0 1

3

5

7

9

11

13

15

17

19

21

23

25

27

Weeks

Existing

Lean Cell

Figure 33Production Volume VI

Shafts and fixtures are produced in more quantity mainly due to lesser work load on the universal mill due to another route for the gears and drills.

Production Volumes

Shafts and Fixtures

10 9 8 7 6 5 4 3 2 1 0 1

3

5

7

9

11

13

15

17

19

21

23

25

Weeks

Existing

Lean Cell

Figure 34 Production Volume VII

Gears are produced in Lean Cell in more quantity than that of Existing Set Up.

76

27

MSc Thesis


Production Volumes

Gears and Gear Shafts

7 6 5 4 3 2 1 0 1

3

5

7

9

11

13

15

17

19

21

23

25

27

Weeks

Existing

Lean Cell

Figure 35 Production Volume

5.6.2.4

Weeks Vs Mean Tardiness

A worst case of the Tardy Jobs in Lean as well as Existing Tool room is shown below. All other cases depict that Lean Cell is capable enough to produce the jobs within the time specified. The Figure shows the comparison of the Lean and Existing Set Up.

6000 4000 2000 0 -2000

Part A

Part B

Part C

Part D

Part E

Part F

Part G

-4000 -6000 -8000 -10000 -12000 Lean Cell Mean Earliness

Lean Cell Mean Tardiness

Existing System Mean Earliness

Existing System Mean Tardiness

Figure 36Comparison of Mean Tardiness

77

Part H

MSc Thesis


5.6.2.5

Weeks Vs Mean Queue Times

Figure shows that mean queue times are lesser in the case of Lean Cells. There are uniform queues in the Lean Cell.

Mean Queue Times

400 300

200 100 0 1

3

5

7

9 11 13 15 17 19 21 23 25 27 Weeks Existing Tool Room

Figure 37Mean Queue Times I

Mean Queue Times

The figure shows that the Mean Queue Times are reduced for the Lean Cell and the queue times are quite near to zero.

300 250 200 150 100 50 0 1

3

5

7

9

11

13

15

17

19

21

23

25

Weeeks

Vertical Grinder-E

Vertical Grinder -L

Figure 38Mean Queue Times II

The figure shows that the Mean Queue Times are reduced for the Lean Cell and the queue times are quite near to zero.

78

27

MSc Thesis


Mean Queue Times

800 700 600 500 400 300 200 100 0 1

3

5

7

9

11

13

15

17

19

21

23

25

27

Weeks

Existing Tool Grinder

Lean Tool Grinder

Figure 39 Mean Queue Times III

Mean Queue Times

In the case of the External Grinder the Queue Times are little better than the existing Tool Room. 160 140 120 100 80 60 40 20 0 1

3

5

7

9

11

13 15 17 Weeks

External Grinder-E

External Grinder-L

Figure 40 Mean Queue Times IV

79

19

21

23

25

27

MSc Thesis

5.7


Case Study 03

This case study is concerned with the One Piece Flow methodology of Lean Manufacturing. The Corn Mill Cutter is produced keeping One Piece and a Batch of 05 parts. The results are quite comparable with the theoretical results.

5.7.1

One Piece Flow Vs Batch Flow:

The following performance measures are considered for comparison of One Piece Flow and Batch Type Production. 1. 2. 3. 4. 5.

Work In Process Inventory Mean Flow Time Resource Utilization Mean Queue Length Throughput

5.7.1.1

Work In Process Inventory:

Figure shows that WIP inventory is quite low compared with batch type production. Less WIP inventory means less cost and more production.

WIP

One Piece Vs Batch Production 45 40 35 30 25 20 15 10 5 0 Mean WIP

Mean WIP

One Piece Flow

Batch Production

4.0556

41.573

Figure 41 Mean WIP in One Piece Flow

5.7.1.2

Mean Flow Time

Figure show mean flow time is less compared with Batch Production. It means reducing the size of the batch ensures more production.

80

MSc Thesis


2500

Mean Flow Time

2000 1500 Mean Flow Time

1000 500 0

Mean Flow Time

One Piece Flow

Batch Type Production

875.01

1914

Figure 42 Mean Flow Time in One Piece Flow

5.7.1.3

Mean Queue Times:

One Piece Flow ensures zero waiting time, and the flow is similar compared with mass production or single model assembly line.

Resource Queue Times

1200 1000 800 600 400 200 0 Tool Grinder

Tool Mill

Vertical Grinder

Centre Lathe


0

118.2

761.8

1092.9

One Piece Flow

0

0

0

0

Figure 43 Mean Queue Times in One Piece Flow

5.7.1.4

Resource Utilization:

The Resource Utilization is better in case of One Piece Flow than Batch Type Production.

81

MSc Thesis


2.5 2 1.5 1 0.5 0 Tool Grinder

Tool Mill

Vertical Grinder

Centre Lathe


0.95487

1.795

0.97255

0.99986

One Piece Flow

0.87994

1.7488

0.92935

0.48627

2

2

1

1

Resource Available

Figure 44 Utilization of Resources in One Piece Flow

5.7.1.5

Mean Queue Lengths:

The queue lengths in case of One Piece Flow are zero. The Batch Type production doesn’t ensure zero queue lengths.

Queue Lengths 30 25 20 15 10 5 0

Tool Grinder

Tool Mill

Vertical Grinder

Centre Lathe


0

0.63104

8.0743

28.12

One Piece Flow

0

0

0

0

Figure 45 Queue Lengths in One Piece Flow

82

MSc Thesis


5.7.1.6

Throughput:

The Throughput is better in One Piece Flow than Batch Type Production.

4.5

3.97

4 3.5 3 2.5 1.87

2 1.5 1 0.5 0


One Piece Flow

1.87

3.97

Throughput

Figure 46 Throughput in One Piece Flow

5.7.1.7

Conclusion

One piece flow always requires zero queue lengths and zero queue times. This case study has verified this theoretical approach. Similarly total throughput has decreased and there are less mean flow times in case of one piece flow.

83

MSc Thesis


84

MSc Thesis


6

Conclusion

Although organization is rich in all types of resources including manpower, money, machine tools etc yet available facilities are not properly utilized. Dependency of major parts produced within the manufacturing factory is a joint venture of Pakistan and China. The resources are not well utilized and are facing the situation of starvation and saturation. Some of the machine tools are excessively over loaded and others are under utilized. These factors make it difficult for the manufacturing as well as rebuild factory to meet the targets. Mixed model production natured workers assignment for different part products make the schedule very complex. Existing setup of the organization has process layout. Research work is aimed at changing the existing layout into cellular layout and then study the effects of this change. In order to compare the effect of the change, some performance measures were taken. Change of the layout into cellular was carried through GT Cell Formation technique. Time study of the processing at shop floor was monitored for about 28 weeks. This data studied provided input distributions or trend of the processing on shop floor. Arena 3.0 was used to implement the modeling using the inputs and the workstations available. To simplify the analysis, following assumptions are made for the rebuild activity; 1. 2. 3. 4.

Set up Times are either nominal or these are included in the Processing Times. The fixtures are designed such that the clamping and holding is not a problem. There are quick changeover techniques. The tool magazine is designed for all the parts and tool is changed with out any interruption within 10 seconds of the processing time.

The results obtained by running the simulation were collected and all the performance measured were compared using excel. It was found that the changed layout has performed better than the existing. If we look at processes, it was worthy to note it that processes were simplified and standardized. All the cells were performing better in meeting targets and can be adjusted to meet the demands by changing the arrival times or transfer times using different techniques of automation. However, it was not possible to verify the proposed layout experimentally. Research work has some problems to cater for the breakdowns and other factors that may cause unexpected stoppage of the working. It is strongly recommended that organization must make the changes in its existing set up to make it a profiteering organization. Currently the organization is running on ―no profit no loss‖ concept. However, it may retain some of its shop floors in the existing layout to provide supporting activities to other organizations.

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MSc Thesis


References 1. Kelton, David, Randall Sadowski and Deborah Sadowski. 1998 Simulation With Arena. McGraw Hill Companies, Boston,MA 2. Law, A.M, and W.D.Kelton. 1991 Simulation Modeling and analysis. 2nd Ed. New York: McGraw –Hill,Inc 3. Pegden, C.D., R.E. Shannon, and R.P. Sadowski. 1995. Introduction to Simulation with SIMAN 2nd Ed. New York: McGraw –Hill, Inc 4. Goldesman, D., (1992), ― Simulation Output Analysis‖ Proceeding of the 1992 Simulation Conference, J.J Swain et al (eds), pp. 97-103 5. Herrmann, J.W., E. Lin, B. Ram, and S. Sarin, Adaptable simulation models for manufacturing, Proceedings of the 10th International Conference on Flexible Automation and Intelligent Manufacturing, Volume 2, pp. 989-995, College Park, Maryland, June 26-28, 2000. 6. Gahagan, Sean M., and Jeffrey W. Herrmann, Improving simulation model adaptability with a production control framework, Proceedings of the 2001 Winter Simulation Conference, B.A. Peters, J.S. Smith, D.J. Medeiros, and M.W. Rohrer, eds., Arlington, Virginia, December, 2001. 7. Chipman, Gene, Catherine Plaisant, Sean Gahagan, Jeffrey W. Herrmann, Sara Hewitt, Lakeisha Reaves, Understanding Manufacturing Systems with a Learning Historian for User-Directed Experimentation. CS-TR-4243, UMIACS-TR-2001-29, University of Maryland, College Park, 2001. 8. Sara T. Hewitt and Jeffrey W. Herrmann, Interfaces to enhance user-directed experimentation with simulation models of discrete-event systems, to appear in Proceedings of the SCS International Conference on Simulation and Multimedia in Engineering Education, Western Multiconference on Computer Simulation, Orlando, Florida, January 19-23, 2003. 9. Sara T. Hewitt, Comparing Analytical and Discrete-Event Simulation Models of Manufacturing Systems, M.S. Thesis, University of Maryland, 2002. 10. Gahagan, Sean M., and Jeffrey W. Herrmann, Finding the optimal production control policy using the production control framework Proceedings of the 2005 Winter Simulation Conference, Orlando, Florida, December 4-7, 2005. 11. Schriber, T.J. The nature and role of simulation in the design of manufacturing systems. Tutorial material presented at 1987 AUTOFACT Conference, Detroit, Michigan, November 10, 1987.

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