• Journal of Korean Institute of Industrial Engineers
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• v.22 no.1
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• pp.141-154
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• 1996

This paper presents a similarity coefficient based approach to the problem of machine-part grouping for cellular manufacturing. The method uses relevant production data such as part type, production volume, routing sequence to make machine cells and part families for cell formation. A new similarity coefficient using weighted factors is introduced and an algorithm for formation of machine cells and part families is developed. A comparative study of two similarity coefficient methods, Gupta and Seifoddini's method and the proposed method, is conducted.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.46
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• pp.59-72
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• 1998

This study is concerned in manufacturing cell formation with operation sequences. Operation sequences must be reflected for manufacturing cell formation anyway, because the primary aim of cellular manufacturing system is to minimize the inter-cell flows, and inter-cell flows are differed by operation sequences. In this study we propose flow-similarity(FS) of reflecting both inter-machine similarity and direct/indirect flow, and then apply the modified P-median model for grouping machines. We also use machine cell-part handling frequency(CPH) so as to be assigned parts to the machine cells having the most CPH. We confirm this approach through an application example. The performance of this approach(FS-model) is evaluated and compared with P-median model and F-model through computational experiments.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.41-50
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• 2000

Cell formation(CF) Is to group parts with similar geometry, function, material and process into part families, and the corresponding machines into machine cells. Cell formation solutions often contain exceptional elements(EEs). Also, the following objective functions - minimizing the total costs of dealing with exceptional elements and maximizing total similarity coefficients between parts - have been used in CF modeling. Thus, multiobjective programming approach can be developed to model cell formation problems with two conflicting objective functions. This paper presents an effective cell formation method with fuzzy multiobjective nonlinear mixed-integer programming simultaneously to form machine cells and to minimize the cost of eliminating EEs.

• IE interfaces
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• v.10 no.3
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• pp.189-196
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• 1997

This paper presents a cell formation approach for a cellular manufacturing system to minimize the inter-cell moves considering operation sequences. Two new factors are introduced: (1)flow-similarity(FS) for integrating direct/indirect inter-machine flow and similarity (2)machine cell-part moves (CPM) for exactly computing inter-cell moves. FS is used for combining machines and CPM is used for assigning the parts to the preliminary machine cells. In addition, we develop an aggregated heuristic algorithm to form manufacturing machine cells and assign the parts to those cells based on these concepts. We use performance criterion called total inter-cell moves(TICM), which is the total material flow between internal cells and external cells. Results of computational tests on a number of randomly generated test problems show that the suggested heuristic is superior to existing methods.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.1
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• pp.20-26
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• 2005

This paper proposes the heuristic algorithm for the generalized GT problems to consider the restrictions which are given the number of machine cell and maximum number of machines in machine cell as well as minimum number of machines in machine cell. This approach is split into two phase. In the first phase, we use the similarity coefficient which proposes and calculates the similarity values about each pair of all machines and sort these values descending order. If we have a machine pair which has the largest similarity coefficient and adheres strictly to the constraint about birds of a different feather (BODF) in a machine cell, then we assign the machine to the machine cell. In the second phase, we assign parts into machine cell with the smallest number of exceptional elements. The results give a machine-part grouping. The proposed algorithm is compared to the Modified p-median model for machine-part grouping.

• IE interfaces
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• v.2 no.2
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• pp.15-24
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• 1989

When we design, plan, and schedule for group technology, the limitation on the machine cells and cell size may occur. The purpose of this study is to find machine cells and part families to minimize the exceptional elements, constraining both the number of machine cells and the cell size. To solve this problem, the algorithm extending Kusiak's p-median method is proposed. In the proposed algorithm, the method finding initial solution and reducing the number of constraints is presented for computational efficiency. The proposed algorithm is evaluated and compared with well-known algorithms for machine-part group formation in terms of the exceptional elements. An example is shown to illustrate the proposed algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.54
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• pp.65-75
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• 2000

Cellular manufacturing(CM) is a philosophy and innovation to improve manufacturing productivity and flexibility. Cell formation(CF), the first and key problem faced in designing an effective CM system, is a process whereby parts with similar design features or Processing requirements are grouped into part families, and the corresponding machines into machine cells. Cell formation solutions often contain exceptional elements(EEs). EE create interactions between two manufacturing cells. A policy dealing with EEs considers minimizing the total costs of three important costs; (1)intercellular transfer (2)machine duplication and (3)subcontracting. This paper presents an effective cell formation method with fuzzy nonlinear mixed-integer programming simultaneously to form manufacturing cells and to minimize the total costs of eliminating exceptional elements.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.4
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• pp.360-367
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• 2002

The machine-part group formation is to group the sets of parts having similar processing requirements into part families, and the sets of machines needed to process a particular part family into machine cells. The purpose of this study is to develop a two-phase machine-part group formation algorithm based on Self-Organizing Maps (SOM). In phase I, it forms machine cells from the machine-part incidence matrix by means of SOM whose output layer is one-dimension and the number of output nodes is the twice as many as the number of input nodes in order to spread out the input vectors. In phase II, it generates part families which are assigned to machine cells by means of machine ratio related with processing part and it gives machine-part group formation. The proposed algorithm performs remarkably well in comparison with many well-known algorithms for the machine-part group formation problems.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.2
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• pp.25-33
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• 1992

Manufacturing cell formation is one of the most important problems faced in designing cellular manufacturing systems. The purpose of this study is to design effective manufacturing cell systems by developing a method which forms machines/parts into optimal machine cells/part families. The 0-1 data matrix structure is used to form a basis for manufacturing cell formation. In this paper, we propose a CE method to reorder the 0-1 data matrix for manufacturing cell formation. The resulting solutions are shown to demonstrate the effectiveness of the CE method.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.2
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• pp.45-55
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• 1986

A method for forming production cells in cellular manufacturing systems is presented. The basic approach is based on part-machine group formation by using relationship matrix calculated from the original part-machine matrix. The cases of exceptional elements and bottleneck machines are discussed. The proposed method can work with any starting form of part-machine matrix and provides the same solution regardless of the changes of starting form of part-machine matrix for any given problem.