Iterature Review Cellular Manufacturing And Group Technology

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Implementation of Cellular Manufacturing And Group Technology

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Iterature Review Cellular Manufacturing And Group Technology

  1. 1. Literature Review on Group Technology and Cellular Manufacturing By Sandeep Bagul
  2. 2. Cellular Manufacturing: Introduction: In today’s business world, competitiveness defines an industry leader. The drive toward maximum efficiency is constantly at the forefront of such companies’ objectives. Managers across the country are striving to adopt lean manufacturing practices to help address worries about their bottom line. Cellular Manufacturing is one staple of lean manufacturing. Cellular Manufacturing is an approach that helps build a variety of products with as little waste as possible. A cell is a group of workstations, machine tools, or equipment arranged to create a smooth flow so families of parts can be processed progressively from one workstation to another without waiting for a batch to be completed or requiring additional handling between operations. Put simply, cellular manufacturing group’s together machinery and a small team of staff, directed by a team leader, so all the work on a product or part can be accomplished in the same cell eliminating resources that do not add value to the product. How to incorporate cellular manufacturing? The implementation process of shedding the traditional manufacturing processes and embracing the drastically different cellular manufacturing techniques can be a daunting task. Management must deal with many issues including: cell design and set up, team design and placement, employee training, teamwork training, as well as other company functional issues. A project team should be put together that consists of management and production employees to handle these changes.
  3. 3. Cell Design and Setup: It should be executed to facilitate the movement of the product through its production cycle and should also be able to produce other similar products as well. The cells are arranged in a manner that minimizes material movement and are generally set up in a “U” shaped configuration. Team Design and Placement is a crucial part of the process. Employees must work together in cell teams and are led by a team leader. This team leader becomes a source of support for the cell and is oftentimes responsible for the overall quality of the product that leaves his/her cell. Employee Training must also accompany the change to cellular manufacturing. In cellular manufacturing workers generally operate more that one machine within a cell which requires additional training for each employee creating a more highly skilled workforce. This cross- training allows one employee to become proficient with his/her machines and while also creating the ability to operating other machines within the cell when such needs arise. Teamwork Training should generate camaraderie within each cell and stimulate group related troubleshooting. Employees within each team are empowered to employ ideas or processes that would allow continuous improvement within the cell, thus reducing lead times, removing waste and improving the overall quality of the product.
  4. 4. Other issues that must be addressed include changes in purchasing, production planning and control, and cost accounting practices. Arranging people and equipment into cells help companies meet two goals of lean manufacturing: one-piece flow and high variety production. These concepts dramatically change the amount of inventories needed over a certain period of time. • One-piece flow is driven by the needs of the customer and exists when products move through a process one unit at a time thus eliminating batch processing. The goals of once-piece flow are to produce one unit at a time continuously without unplanned interruptions and without lengthy queue times. • High-variety production is also driven by the needs of the customer who expect customization as well as specific quantities delivered at specific times. Cellular manufacturing provides companies the flexibility to give customers the variety they demand by grouping similar products into families that can be processed within the same cell and in the same sequence. This eliminates the need to produce products in large lots by significantly shortening the time required for changeover between products. In order to set up a single process flow (or single product flow) line, it is necessary to locate all the different equipment needed to manufacture the product together in the same production area. This is in contrast with the traditional 'batch and queue' set-up wherein only similar equipment is put in the same area. Under a 'batch and queue' set-up, products that need to undergo processing under certain equipment need to be transported to the area where the equipment is located. There
  5. 5. they are queued for processing in batches. Such a system sometimes results in transport and batching delays. In a single process flow set-up, the products simply transfer from one equipment to the next along the same production line in a free-flowing manner, avoiding transport and batching delays. The single process flow set-up described above is an example of a 'work cell'. A work cell is defined as a collection of equipment and workstations arranged in a single area that allows a product or group of similar products to be processed completely from start to finish. It is, in essence, a self-contained mini-production line that caters to a group of products that undergo the same production process. Cellular manufacturing involves the use of work 'cells', which is how it got its name. Since differently-processed products need different work cells, a large company with diversified products needs to build several, different work cells if single process flows are desired. Given enough volume of products to work with, work cells have been proven by experience to be faster and more efficient in manufacturing than 'batch and queue' systems. Because of the free flow of materials in cellular manufacturing, it has the ability to produce products just in time. This means that every unit processed at one station will get processed in the next station. As such, no inventories that have already undergone processing at one station will be left unprocessed in another station. This prevents the build-up of non-moving inventories, which are products that have already incurred some production costs but can not generate revenues because they are stuck somewhere along the process. Aside from preventing
  6. 6. non-moving inventories, process issues are immediately detected by just-in-time production, since defective products are seen earlier than if products are manufactured in large batches and queued. One technique that cellular manufacturing can use to achieve 'just-in-time' production is the 'pull system', wherein required inventories and materials are requested or 'pulled in' by each station from the station preceding it. This 'pull' can originate from the end customer itself, thereby ensuring that the products manufactured are only those needed to satisfy a customer order. This prevents wastes from products not being sold. It is not enough to simply arrange different equipment in sequence to make cellular manufacturing really work. Bottlenecks along the single process flow must be eliminated, usually by balancing the equipment capacities with each other. If bottlenecks exist, then the higher-capacity equipment within the line will be underutilized. Balancing equipment capacities may mean: 1) choosing 'right-sized' equipment that match each other; and/or 2) combining two or smaller capacity equipment to match one larger-capacity equipment.
  7. 7. Literature Overview: Case Study on Scheduling for Cellular Manufacturing Roman van der Krogt, James Little, Kenneth Pulliam, Sue Hanhilammi, & Yue Jin (2007) found Alcatel-Lucent is a major player in the field of telecommunications. One of the products it offers to network operators is wireless infrastructure such as base stations. Such equipment is delivered in cabinets. These cabinets are packed with various pieces of electronics: filters, amplifiers, circuit packs, etc. The variation in cabinets is large, even within one product group. For this reason, they are built to order. In order to improve cost, yield and delivery performance, lean manufacturing concepts were applied to change the layout of the factory to one based on cells. These cells focus on improving manufacturing through standardized work, limited changeovers between product groups and better utilization of test equipment. A key component in the implementation of these improvements is a system which schedules the cells to satisfy customer request dates in an efficient sequence. This paper describes the transformation that supports the new method of operations which shows improvements in manufacturing interval, work in process inventory, first test yield, headcount, quality (i.e. fewer defects are found during the testing stage) and delivery performance. Although these benefits are mainly achieved because of the change to a cell layout, the scheduling tool is crucial in realizing the full potential of it. The exact configuration of a cabinet is dependent upon the type of network (e.g. CDMA or UMTS), the frequency (the GSM standard defines eight frequency bands, for example), physical location (inside or outside), network density (is it expected to handle a high or low volume of calls, what is the area the cabinet covers), etc.
  8. 8. The Systems Integration Center in Columbus, Ohio, produces several hundred cabinets per week on average. The production takes place in three stages: assembly, wiring and testing. The durations of each stage depends on the particular product group of the cabinet. • Assembly: The first series of steps takes as input a partially pre-populated cabinet. • Wiring: The second step involves physically interconnecting the hardware that was added during assembly. • Testing: The final step involves the validation of the completed system. Of the three stages, assembly is a relatively low skill operation and requires the least amount of training. The wiring step is more complicated, because a great number of connections have to be made between a great numbers of connectors that all look identical. There is a high degree of freedom in the way the connections can be made. Not in terms of the inputs and outputs that have to connected (these are fixed), but in terms of the order in which the connections are made (i.e. which cables run in front of other cables), the position of the cables (e.g. along the left or the right side of the cabinet) and which cables are tied together. The final step of testing is also complicated, as it involves making diagnoses for the detected anomalies and repairing them. The wirers and test engineers face a great difficulty because of the huge variety in cabinets. Assembly puts populated cabinets into a buffer, from which the wirers take their cabinets. In their turn, wirers put finished cabinets into a buffer for testing. In this situation, only a very crude scheduling is employed. Based on the due dates of the orders, it is decided which orders are to be produced on a given day. The assembly stage then starts populating the required cabinets and places them in a buffer for wiring. When a wirer finishes a cabinet, he chooses one of the cabinets from the buffer to work on. Similarly, testers pull a cabinet out of the buffer for testing. In this way, cabinets trickle down the three stages on their way to completion. Aside from the
  9. 9. selection of which orders to produce on a given day, no scheduling is performed. This may lead to several issues. Moreover, cabinets from product groups that are hard to wire may have to wait in the wiring buffer for a long time, since other, easier, cabinets are preferred by the wirers. To prevent these and similar issues, management had decided to move from what was essentially an assembly line to a (partially) cell-based work floor. In particular, the company wanted to integrate the wiring and testing activities into a cell, as depicted in Fig b. From assembly line to cell-based work floor Current Research Constraint-based scheduling is a modeling and solving technique successfully used to solve real- world manufacturing problems in, for example, aircraft manufacturing, production scheduling and the semiconductor industry. In the area of telecommunications, the area of cellular manufacturing is more about layout and design. The Author Ponnabalam et al.consider simulation of manufacturing through a cell in light of uncertainty. They propose new heuristics to decide on the allocation of jobs to machines. Here the user interface is built in Microsoft Excel
  10. 10. using Visual Basic. It allowed for easy integration with the existing Work floor Management System that tracks all activities and can generate reports in the Excel file format for initial modeling and getting the feedback on that model. The amount of work it takes to go from prototype to a system robust is enough to withstand user interaction which allows for different input profiles. In this case it is important to make the user realize that the initial phase of testing will be slow and not very smooth at times, as the tool is adjusted to match the reality on the shop floor. Future Research Work This project shows the strength of the combination of lean manufacturing techniques and (CP- based) scheduling. The former techniques allow a business to take a critical look at its operations to identify areas for improvement, whereas the latter technique can be used to realize the potential of the improvements. The amount of constraints the program has to handle points out the need for it. Scheduling manually would not allow us to service our customers as well. The engineers at the site had experience with the Theory of Constraints to help greatly in the initial modeling and getting the feedback on that model. The amount of work it takes to go from prototype to a system robust enough to withstand user interaction is considerable. Moreover, the variety of situations that is encountered in practice means that the model itself has to be robust enough to allow for very different input profiles. This either calls for a large data set during development, or a period of building this robustness during the testing process. In this case it is important to make the user realize that the initial phase of testing will be slow and not very smooth at times, as the tool is adjusted to match the reality on the shop floor.
  11. 11. Related Journals Supporting the above Literature Review: Partitioning bottleneck work center for cellular manufacturing: An integrated performance and cost model (Atul Agarwal, 2007) The objective of this paper is to investigate performance and cost issues in an integrated manner during conversion of an existing functional layout by partitioning it to a corresponding cellular manufacturing (CM) layout. Decision frameworks presented which provides a systematic approach to a practitioner for such a conversion. A total cost model is developed to study the performance and financial aspects for the CM system. The relationship between setup time reduction and the operational characteristics of a cell is also examined. A simple case study from a small manufacturing organization is used to evaluate the practical dimensions of the model and study results. A decision support tool to facilitate the design of cellular manufacturing layouts V. Vitanov, B. Tjahjono, & I. Marghalany (2007) found This paper presents a decision support tool that can be used by practitioners and industrialists to solve practical cell formation problems. The tool is based on a cell formation algorithm that employs a set of heuristic rules to obtain a quasi-optimal solution from both component routing information and other significant production data. The algorithm has-been tested on a number of ata sets obtained from the literature. The test results have demonstrated that in many cases the algorithm has produced an exceptional performance in terms of the grouping efficiency, grouping efficacy and quality
  12. 12. Index measures. The algorithm, to an extent, overcomes common problems in existing cell formation methods such as in dealing with ill-structured matrices and achieving rational cell sizes. A genetic algorithm for cellular manufacturing design and layout Xiao Dan Wu, Chao-Hsien Chu, Yunfeng Wang, & Weili Yan (2006) found Cellular manufacturing (CM) is an approach that can be used to enhance both flexibility and efficiency in today’s small-to-medium lot production environment. The design of a CM system (CMS) often involves three major decisions: cell formation, group layout, and group schedule. Ideally, these decisions should be addressed simultaneously in order to obtain the best results. However, due to the complexity and NP-complete nature of each decision and the limitations of Traditional approaches, most researchers have only addressed these decisions sequentially or independently. In this study, a hierarchical genetic algorithm is developed to simultaneously form manufacturing cells and determine the group layout of a CMS. The intrinsic features of our proposed algorithm include a hierarchical chromosome structure to encode two important cell design decisions, a new selection scheme to dynamically consider two correlated fitness functions, and a group mutation operator to increase the probability of mutation. From the computational analyses, these proposed structure and operators are found to be effective in improving solution quality as well as accelerating convergence.
  13. 13. A goal-programming approach for design of hybrid cellular manufacturing systems in dual resource constrained environments (Sule Itir Satoglu & Nallan C. Suresh, 2008) In this study, a goal-programming model is proposed for the design of hybrid cellular manufacturing (HCM) systems, in a dual resource constrained environment, considering many real-world application issues. The procedure consists of three phases. Following an initial phase involving a Pareto analysis of demand volumes and volatility, a machine-grouping phase is conducted to form manufacturing cells, and a residual functional layout. In this phase, over- assignment of parts tithe cells, machine purchasing cost, and loss of functional synergies are attempted to be minimized. Following the formation of cells and the functional layout, a labor allocation phase is carried out by considering worker capabilities and capacities. The total costs of cross-training, hiring, firing and over-assignment of workers to more than one cell are sought to be minimized. An application of the model on real factory data is also provided in order to demonstrate the utility and possible limitations. The industrial problem was solved using professional mathematical programming software. A new approach for the cellular manufacturing problem in fuzzy dynamic conditions by a genetic algorithm R. Tavakkoli-Moghaddama, M.B. Aryanezhad, N. Safaei, M. Vaseia, & A. Azaronc (2007) This paper presents a fuzzy linear mix-integer programming model for design of cellular manufacturing systems with fuzzy part demands and product mix changeable under a multi- period planning horizon. In this dynamic condition, the best cell design for one period may not be efficient for subsequent periods and the reconfiguration of cells is required. The proposed model can determine the production volume for each part considering its fuzzy demand. The
  14. 14. other advantages of the proposed model are as follows: considering inter-cell material handling with constant batch size, alternative process plan forepart types, operation sequence, machine relocation, machine replication, machine utilization and cell number flexibility. Main constraints are the cell size, machine capacity and production volume limitations. The objective is to minimize the sum of the constant/variable/relocation machine costs as well as inter-cell movements cost. Because of the complexity of the proposed model, which is a combinatorial nonlinear optimization, we develop an efficient genetic algorithm with novel representation and Operators for solving the proposed model. 29 small, medium and large-sized problems are generated to evaluate the performance of the proposed model and the efficiency of the developed genetic algorithm. An algorithm for cellular manufacturing system and layout design using sequence data (Iraj Mahdav & B.Mahadevan, 2007) Cell formation problem in CMS design has received the attention of researchers for more than three decades. However, use of sequence data for cell formation has been a least researched area. Sequence data provides valuable information about the flow patterns of various jobs in a manufacturing system. Therefore, it is only natural to expect that use of sequence data must result in not only identifying the part families and machine groups but also the layout (sequence) of the machines within each cell. Unfortunately, such an approach has not been taken in the past while solving CMS design problem using sequence data. In this paper, we fill this gap in the Literature by developing an algorithm that not only identifies the cells but also the sequence of machines in the cells in a simultaneous fashion. The numerical computations of the algorithm with the available problems in the literature indicate the usefulness of the algorithm. Further, it
  15. 15. also points to the untapped potential of such an approach to solve CMS design and layout problem using sequence data. An optimal design approach for a cellular manufacturing system R Giri, J Srinivas, & K V V C Mouli (2007) found The current paper proposes an optimum clustering approach for automatic generation of machine cells and part families. The design of a cellular manufacturing system begins with a specified ‘part-machine incidence’ matrix, showing the machine sequence and volume of production. The arrangement of machines in the cells is addressed in the present paper by finding an optimal machine sequence, which maximizes the overall flow of components between the machines. An optimal number of cells are arrived heuristically by accounting the total intercool movements using the obtained machine sequence. The methodology is illustrated with examples. Cellular manufacturing—A time-based analysis to the layout problem (Mechanical Engineering Department, [N.I.T], 2007) A cellular manufacturing system is an application of group technology principles to production. This involves processing groups of similar components in a dedicated cluster of dissimilar machines. In this paper, an approach that forms the cluster based on the processing time is suggested. For even distribution of workload, workload balancing is carried out in the second phase of the model, i.e., a time-based model. The time-based model is compared with the workload-based model using a commonality score. The performance of the time-based model is compared by means of workload deviation and deviation index. The validity of the approach is tested by application to the problems from the literature and the results are presented. The results
  16. 16. indicate that the time-based model gives better even distribution of workload as compared to the workload-based model. Layout designs in cellular manufacturing (Massoud Bazargan-Lari, 1997) Cellular manufacturing (CM) is now an established international practice to integrate: equipment, people, and systems into `focused factories', `mini-businesses' or `cells' with clear customers, responsibilities and boundaries. The major elements in exploiting the beets of CM are client layout designs. This paper presents the application of recently developed multi-objective inter- and intra-cell layout designs methodologies in a CM environment by the author To a dynamic food manufacturing and packaging company in Australia. Some of the problems expressed by the company were large and unnecessary volume of shop floor material handling cost, di チ culties and confusion overproduction planning, long products lead times resulting in losing customers and high overhead costs. Furthermore the company was deeply concerned about the increasing number of accidents and injuries on the shop floor caused by poor Layout of machinery and the lack of proper aisle structures for movement of the lift-trucks. This paper shows the process of developing the inter-cell layout designs by providing the management with multiple layout configurationsand showing the impact of each design on the material handling cost at each stage. These solutions not only provide a safer shop floor but also signi®cant reductions in material handling cost, waste, need for large capital investment and the number of lift-trucks needed on the shop Floor.
  17. 17. Reliability consideration in the design and analysis of cellular manufacturing systems (K. Das, S Lashkari, & S. Sengupta, 2006) A multi-objective mixed integer programming model of cellular manufacturing system (CMS) design is presented which minimizes the total system costs and maximizes the machine reliabilities along the selected processing routes. A part maybe processed under different process plans, each prescribing a sequence of operations to be performed at various machines in a serial configuration. Thus, each process route is associated with a level of reliability corresponding to the machines in the selected process plan. The CMS design problem consists of assigning the machines to cells, and selecting, for each par type, the process route with the highest overall system reliability while minimizing the total costs of manufacturing operations, machine under- utilization, and inter-cell material handling. The proposed approach provides a flexible routing Which ensures high overall performance of the CMS by minimizing the impact of machine failure through the provision of alternative process routes in case of any machine failure? The paper also proposes performance evaluation criterion interims of system availability for the parts and process plan assignments. Numerical examples are provided to demonstrate the applicability of the model. The evolution of a cellular manufacturing system – a longitudinal case study (cult of Management and Organization, University of Groningen, 2001) This paper describes the evolution of a cellular manufacturing system in a medium-sized company over a 13-yearperiod. The objective of this paper is to analyze the arguments that gave rise to the nearly continuous readjustment of the design of the cellular manufacturing system of
  18. 18. this company and the direction in which these adjustments took place. The study indicates that two interrelated factors played an important role in the decision to change the system: The market and manufacturing technology. Analysis of these factors offers important insights into the aspects that need to be taken into account in cell formation. It is argued that a cellular system should reflect market characteristics. New technology, furthermore, demands specialized cells, producing in a multi-shift situation. These two developments pointing the direction of market-oriented, reasonably sized, functionally organized manufacturing units. It is argued that Market developments, new manufacturing technology and modern production control systems will probably constraint the application area of cellular manufacturing Multi-period planning and uncertainty issues in cellular manufacturing: A review and future directions (Jaydeep Balakrishnan &hun Hung Cheng, 2006) In this paper we review research that has been done to address cellular manufacturing under conditions of multi Period planning horizons, with demand and resource uncertainties. Most traditional cell formation procedures ignore any changes in demand over time caused by product redesign and uncertainties due to volume variation, part mix variation, and resource unreliability. However in today’s business environment, product life cycles are short, and demand volumes and product mix can vary frequently. Thus cell design needs to address these issues. It is only recently that researchers have been modeling uncertainty and multi-period issues. In this paper we conduct a comprehensive review of the work that addresses these issues. We present mathematical programming formulations as well as taxonomy of existing models. Finally we suggest some directions for future research
  19. 19. References: Partitioning bottleneck work center for cellular manufacturing: An integrated performance and cost model (Atul Agarwal, 2007) Scheduling for Cellular Manufacturing Roman van der Krogt, James Little, Kenneth Pulliam, Sue Hanhilammi, & Yue Jin (2007) found A decision support tool to facilitate the design of cellular manufacturing layouts V. Vitanov, B. Tjahjono, & I. Marghalany (2007) found A genetic algorithm for cellular manufacturing design and layout Xiaodan Wu, Chao-Hsien Chu, Yunfeng Wang, & Weili Yan (2006) found A goal-programming approach for design of hybrid cellular manufacturing systems in dual resource constrained environments (Sule Itir Satoglu & Nallan C. Suresh, 2008) A new approach for the cellular manufacturing problem in fuzzy dynamic conditions by a genetic algorithm R. Tavakkoli-Moghaddama, M.B. Aryanezhad, N. Safaei, M. Vaseia, & A. Azaronc (2007) An algorithm for cellular manufacturing system and layout design using sequence data (Iraj Mahdav & B.Mahadevan, 2007)
  20. 20. An optimal design approach for a cellular manufacturing system R Giri, J Srinivas, & K V V C Mouli (2007) found Cellular manufacturing—A time-based analysis to the layout problem (Mechanical Engineering Department, [N.I.T], 2007) Layout designs in cellular manufacturing (Massoud Bazargan-Lari, 1997) Reliability consideration in the design and analysis of cellular manufacturing systems (K. Das,S Lashkari, & S. Sengupta, 2006) The evolution of a cellular manufacturing system – a longitudinal case study (culty of Management and Organization, University of Groningen, 2001) Multi-period planning and uncertainty issues in cellular manufacturing: A review and future directions (Jaydeep Balakrishnan &hun Hung Cheng, 2006)

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