• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.589-594
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• 1991

Group Technology (GT) is a technique for identifying and bringing together related or similar components in a production process in order to take advantage of their similarities by making use of, for example, the inherent economies of flow production methods. The process of identification, from large variety and total of components, of the part families requiring similar manufacturing operations and forming the associated groups of machines is referred as 'machine-component grouping'. First part of this paper is devoted to describing a hierarchical divisive algorithm based on graph theory to find the natural part families. The objective is to form components into part families such that the degree of inter-relations is high among components within the same part family and low between components of different part families. Second part of this paper focuses on establishing cell design procedures. The aim is to create cells in which the most expensive and important machines-called key machine - have a reasonably high utilization and the machines should be allocated to minimize the intercell movement of machine loads. To fulfil the above objectives, 0-1 integer programming model is developed and the solution procedures are found. Next an attempt is made to test the feasibility of the proposed method. Several different problems appearing in the literature are chosen and the results air briefly showed.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.705-718
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• 1996

A similarity coefficient based algorithm is proposed to solve the machine cells and part families formation problem in group technology. Similarity coefficients are newly designed from the machine-part incidence matrix. Machine cells are formed using a recurrent neural network in which the similarity coefficients are used as connection weights between processing units. Then parts are assigned to complete the cell composition. The proposed algorithm is applied to 30 different kinds of problems appeared in the literature. The results are compared to those by the GRAFICS algorithm in terms of the grouping efficiency and efficacy.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.122-129
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• 1995

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 coefficients - Gupta and seifoddini's method and proposed method - is conducted. A software program using TURBO C has been developed to verify the implementation.

• 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.

• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.1
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• pp.121-128
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• 2005

This paper proposes the heuristic approach for the generalized GT(Group Technology) problem to consider the restrictions which are given the number of cell, maximum number of machines and minimum number of machines. This approach is classified into two stages. In the first stage, we use the similarity coefficient method which is proposed and calculate the similarity values about each pair of all machines and align these values in descending order. If two machines which is selected is possible to link the each other on the edge of machine cell and they don't have zero similarity value, then we assign the machines to the machine cell. In the second stage, it is the course to form part families using proposed grouping efficacy. Finally, machine-part incidence matrix is realigned to block diagonal structure. The results of using the proposed approach are compared to the Modified p-median model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.38
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• pp.9-15
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• 1996

The purpose of this research is to develop a method for part-machine grouping subject to production and management constraints. In the proposed integer programming model, minimization of operating and material-handling costs are considered as an objective function. The model allows one to recognize the existing parts and machines into disaggregated cells. New constraints are introduced in the model to resolve unbalancing capacity and bottleneck problems. It is found that this approach could have a better flexibility on cell size design for mote alternatives than conventional methods. Experimental grouping and comparison studies with ROC algorithm are given for evaluation purposes.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.259-262
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• 2003

Group technology(GT) is a manufacturing philosophy which identifies and exploits the similarity of parts and processes in design and manufacturing. A specific application of GT is cellular manufacturing. the first step in the preliminary stage of cellular manufacturing system design is cell formation, generally known as a machine-part cell formation(MPCF). This paper presents and tests a grouping gentic algorithm(GGA) for solving the MPCF problem and uses the measurements of e(ficacy. GGA's replacement heuristic used similarity coefficients is presented.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.390-396
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• 2002

This study is concerned with the strict machine-cell and part-family grouping (MCPFG) in cellular manufacturing system design. Most of MCPFG methodologies often suffer from improper assignment of machines and parts in which exceptional machine has more common operations with machines in a cell other than its own cell and exceptional part has more operations through machines in a cell other than the cell corresponding to its own family. This results in the loss of similarity in part design or common setup of machines and the benefits from the conversion of job shop manufacturing into cellular manufacturing are lost. In this study, a two-phase methodology is proposed to find the machine-cells and part families under the strict constraints in which all machines and parts are assigned to its most proper cells and families. Test results with moderately medium-sized ill-structured MCPFG problems available from the literature show the substantial efficiency of the proposed approach.