• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.123-132
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• 1998

The group formation problem of the machine and part is a very important issue in the planning stage of cellular manufacturing systems. This paper investigates Self-Organizing Map(SOM) neural networks approach to machine-part grouping problem. We present a two-phase algorithm based on SOM for grouping parts and machines. SOM can learn from complex, multi-dimensional data and transform them into visually decipherable clusters. Output layer in SOM network is one-dimensional structure and the number of output node has been increased sufficiently to spread out the input vectors in the order of similarity. The proposed algorithm performs remarkably well in comparison with many other algorithms for the well-known problems shown in previous papers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.23-31
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• 2000

This paper addresses the static operator allocation problem in celluar manufacturing systems(CMS). An assembly environment is considered where each component going into the final product is manufactured in an individual cell. There are m such cells and it is required to manufacture n varieties of products where n>m. An mathematical model and two heuristic algorithms for static operators allocation to the cells to balance workload for minimizing makespan are developed and tested.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.4
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• pp.559-569
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• 1998

Cellular manufacturing system (CMS) has been recognized as an alternative to improve manufacturing productivity in conventional batch-type manufacturing systems through reducing set-up times, work-in-process inventories and throughput times by means of group technology. Most of the studies on the design of CMS assumed that each part has a unique process plan, and that its demand is known as a deterministic value despite of the probabilistic nature of the real world problems. This study suggests an approach for designing CMS, considering both alternative process plans and uncertain demand. A mathematical model is presented to show how to minimize the expected amortized and operating costs satisfying these two relaxations. Four heuristic algorithms are developed based on tabu search which is well suited for getting an optimal or near-optimal solution. Example problems are carried out to illustrate the heuristic algorithms and each of them is compared with the deterministic counterpart.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.49
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• pp.67-76
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• 1999

This research presents the relationship among machining time, cycle time and demand rate in a cellular manufacturing system. The manufacturing cell produces part families by automated machines. This paper discusses the cases of increasing demand rate in an existing cell and designing cell based on the demand rate. This research developed an algorithm for decision making such as cycle time, machines and workers in order to minimize the total machine capacity and the number of workers for any given demand rate. The proposed algorithm was successfully applied for the design and operation of cell manufacturing with a good result.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.1
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• pp.17-28
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• 1998

This study suggests a procedure for designing cellular manufacturing systems (CMS) which are combined with automated guided vehicles (AGVs) using a tandem configuration. So far most of the previous studies have dealt with conventional design problems not considering the layout and the characteristics of transporters used in CMS. A mathematical model is developed using the service time to perform material transfers as a suitable meassure. The service capacity of AGVs and space limitations are also reflected in this model. As the model can be shown strongly NP-hard, a heuristic algorithm is presented, in which each cell is temporarily formed using both the set covering model and similarity coefficients, and then locations of the cells are determined by means of tabu search and finally machine perturbations are carried out. An example problem is solved to demonstrate the algorithm developed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.125-130
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• 1996

This study is concerned with a heuristic algorithm that can make effectively the machine-part grouping in early stage for designing cellular manufacturing systems. By enhancing the Close Neighbour Algorithm(CNA), the proposed algorithm is concerned with making the machine-part grouping that can maximize machine utilization and minimize part's intercell movement by reducing exceptional elements. The algorithm is tested against existing algorithms in solving several machine-part initial matrices extracted from references and obtained by using random number. Test results shows that a solution matrix of the algorithm has superior grouping efficiency to Close Neighbour Algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.4
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• pp.133-149
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• 1997

The major two steps required to design a cellular layout are cell formation and cell layout. Because of the differences between manufacturing and assembly operations, the logic of cell formation and cell layout between an FMS and an FAS is not the same. Since the time for the assembly operations is usualaly relatively short, the transfer time is thus very crucial for the performance of assembly systems. Transfore in a cellular FAS it is more important to eliminate backtracking operations in assembly planning, not to allow intercellular movements in cell formation, and to arrange machines according to assembly sequence in cell layout. This study presents a method for the integrated layout design in cellular FASs considering the characteristics of FAS, layout, and production factors.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.1
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• pp.24-35
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• 2013

A cell formation approach based on cluster analysis is developed for the configuration of manufacturing cells. Cell formation, which is to group machines and parts into machine cells and the associated part families, is implemented to add the flexibility and efficiency to manufacturing systems. In order to develop an efficient clustering procedure, this paper proposes a cluster analysis-based approach developed by incorporating and modifying two cluster analysis methods, a hierarchical clustering and a non-hierarchical clustering method. The objective of the proposed approach is to minimize intercellular movements and maximize the machine utilization within clusters. The proposed approach is tested on the cell formation problems and is compared with other well-known methodologies available in the literature. The result shows that the proposed approach is efficient enough to yield a good quality solution no matter what the difficulty of data sets is, ill or well-structured.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.2
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• pp.94-100
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• 2005

This paper presents the application of integrated mathematical programming approach for the design of cellular manufacturing. The proposed approach is carried out in two phases The first phase concerning exceptional elements(EEs) in cell formation and the second phase facilities layout design. This paper considers the total costs of three important costs for (1) intercellular transfer (2) machine duplication and (3) subcontracting. One of Important issue is the calculation of the number of machines considering the maximum utilization of machines and the available capacity of a machines that can be transferred between cells. Facilities layout design is considered to reflect the real field data taking in to account the operational sequence of the parts to be manufactured. The model is formulated as mixed integer programming that is employed to find the optimal solution.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.87-96
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• 1998

Using the concept of cellular manufacturing systems(CMS) in job shop manufacturing system is one of the most innovative approaches to improving plant productivity. However. several constraints in machine duplication cost, machining capability, cell space capacity, intercell moves and exceptional elements(EEs) are main problems that prevent achieving the goal of maintaining an ideal CMS environment. Minimizing intercell part traffics and EEs are the main objective of the cell formation problem because it is a critical point that improving production efficiency. Because the intercell moves could be changed according to the sequence of operation, it should be considered in assigning parts and machines to machine ceil. This paper presents a method that eliminates EEs under the constraints of machine duplication cost and ceil space capacity attaining two goals of minimizing machine duplications and minimizing intercell moves simultaneously. Developing an algorithm that calculates the machine duplications by cell-machine incidence matrix and part-machine Incidence matrix, and calculates the exact intercell moves considering the sequence of operation. Based on the number of machine duplications and exact intercell moves, the goal programming model which satisfying minimum machine duplications and minimum intercell moves is developed. A linear programming model is suggested that could calculates more effectively without damaging optimal solution. A numerical example is provided to illustrate these methods.