• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.2
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• pp.94-103
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• 2019

Self Organizing Map (SOM) is a neural network that is effective in classifying patterns that form the feature map by extracting characteristics of the input data. In this study, we propose an algorithm to determine the cell formation and the machine layout within the cell for the cell formation problem with operation sequence using the SOM. In the proposed algorithm, the output layer of the SOM is a one-dimensional structure, and the SOM is applied to the parts and the machine in two steps. The initial cell is formed when the formed clusters is grouped largely by the utilization of the machine within the cell. At this stage, machine cell are formed. The next step is to create a flow matrix of the all machine that calculates the frequency of consecutive forward movement for the machine. The machine layout order in each machine cell is determined based on this flow matrix so that the machine operation sequence is most reflected. The final step is to optimize the overall machine and parts to increase machine layout efficiency. As a result, the final cell is formed and the machine layout within the cell is determined. The proposed algorithm was tested on well-known cell formation problems with operation sequence shown in previous papers. The proposed algorithm has better performance than the other algorithms.

• 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.12 no.4
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• pp.532-539
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• 1999

The first step to design a cellular manufacturing system is to make part-families and machine-cells. This process is called the machine-part grouping. This paper considers a machine-cell size when grouping machine-cells. By considering a machine-cell size, an unrealistically big size of machine-cell which may be caused by the chaining effect can be avoid. A heuristic algorithm which minimizes the number of inter-cell movement of parts considering a machine-cell size is presented. The effectiveness and performance of the proposed heuristic algorithm are compared with those of several heuristic algorithms previously reported. The comparison shows that the proposed heuristic algorithm is efficient and reliable in minimizing the number of inter-cell movement of parts and also prevents the chaining effect.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.1
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• pp.1-9
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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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.263-266
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• 1998

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 ideal Cellular Manufacturin System (CMS) environment. Minimizing intercell part traffics and EEs are the main objective of the cell formation problem as it's 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 cells. This paper presents a method that eliminates EEs under the constraints of machine duplication cost and cell 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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.121-124
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• 1996

In general, cellular manufacturing system can be constructed by the following two steps. The first step forms machine cells and part families, and the second step determines cell layout based on the result of first step. Cell layout has to be considered when cell is formed becauese the result of cell formation affects it. This paper presents a cell formation algorithm and proposes an integrated mathematical model for cell formation and cell layout. The cell formation algorithm minimizes the number of exceptional element in cellular manufacturing system. New concept for similarity and incapability is introduced, based on machine-operation incidence matrix and part-operation incidence matrix. One is similarity between the machines, the other is similarity between preliminary machine cells and machines. The incapability identifies relations between machine cells and parts. In this procedure, only parts without an exceptional element are assigned to machine cell. Bottleneck parts are considered with cell layout design in an integrated mathematical model. The integrated mathematical model determines cell layout and assigns bottleneck parts to minimize the number of exceptional element and intercell moving distance, based on linearixed 0-1 integer programming. The proposed algorithm is illustrated by using numerical examples.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.84-89
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• 2004

The machine cell formation problem is the problem to group machines into machine families and parts into part families so as to minimize bottleneck machines, exceptional parts, and inter-cell part movements in cellular manufacturing systems and flexible manufacturing systems. This paper proposes a new machine cell formation method based on the adaptive Hamming net which is a kind of neural network model. To show the applicability of the proposed method, it presents some experiment results and compares the method with other cell formation methods. From the experiments, we observed that the proposed method could produce good cells for the machine cell formation problem.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.12
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• pp.72-80
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• 1998

In this study, a design approach based on genetic algorithm is proposed to solve the manufacturing cell design problem considering alternative process plans and alternative machines. The problem is formulated as a 0-1 integer programming model which considers several manufacturing parameters, such as demand and processing time of part, machine capacity, manufacturing cell size, and the number of machines in a machine cell. A genetic algorithm is used to determine process plan for each part, part family and machine cell simultaneously.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1565-1568
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• 1997

In this paper, a fuzzy based machine-cell formation algorithm for cellular manufacturing is presented. The fuzzy lovic is employed to express the degree of appropriateness when alternative machnies are specified to process a part shape. For machine grouping, the similarity coefficient based approach is used. The algorithm produces efficient machine cells and part families which maximize the similarity values.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.3
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• pp.305-310
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• 1997

In this paper, a fuzzy set based machine-cell formation algorithm for cellular manufacturing is presented. The fuzzy logic is emoloyed to express the degree of appropriateness when alternative machines are specified to process a part shape. For machine grouping, the similarity coefficient based approach is used. The algorithm produces efficient machine cells and part families which maximize the similarity values.