Fuzzy Part Family Formation Based on Grey Relational Analysis

Part family formation is one of the most important techniques in computer-aided process planning (CAPP). This paper presents a new method that uses grey relational analysis and fuzzy clustering to form part families. The main objective of this paper is to identify part families based on a new similarity coefficient which considers processing time, lot size, machine usability, etc., by using grey relational analysis. After the similarity coefficient is calculated, a fuzzy clustering method is used to obtain part families. The main contribution of this paper is to provide a rigorous mathematical approach to forming part families. Part family formation can be controlled, for different applications, by setting a resolution threshold, so the approach is flexible, practical and reliable.

[1]  S. Gottwald,et al.  Fuzzy sets, fuzzy logic, fuzzy methods with applications , 1995 .

[2]  Inyong Ham,et al.  Multiobjective cluster analysis for part family formations , 1986 .

[3]  D. A. Milner,et al.  Direct clustering algorithm for group formation in cellular manufacture , 1982 .

[4]  Christian Blume,et al.  Computer-integrated manufacturing technology and systems , 1985 .

[5]  Charles S. Snead.  Group technology : foundation for competitive manufacturing , 1989 .

[6]  Hamid R. Parsaei,et al.  Part family formation based on a new similarity coefficient which considers alternative routes during machine failure , 1998 .

[7]  Madan M. Gupta,et al.  Fuzzy mathematical models in engineering and management science , 1988 .

[8]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[9]  Tarun Gupta,et al.  Production data based similarity coefficient for machine-component grouping decisions in the design of a cellular manufacturing system , 1990 .

[10]  Tarun Gupta.  Design of manufacturing cells for flexible environment considering alternative routeing , 1993 .

[11]  Richard A. Wysk,et al.  Computer-aided manufacturing , 1991 .

[12]  J. Deng,et al.  Introduction to Grey system theory , 1989 .

[13]  Sadaaki Miyamoto,et al.  Fuzzy Sets in Information Retrieval and Cluster Analysis , 1990, Theory and Decision Library.

[14]  Ming Liang,et al.  Machine cell/part family formation considering processing times and machine capacities: a simulated annealing approach , 1998 .

[15]  F. Fred Choobineh,et al.  A framework for the design of cellular manufacturing systems , 1988 .

[16]  A. Kusiak.  The generalized group technology concept , 1987 .

[17]  Chwen-Tzeng Su,et al.  A fuzzy approach for part family formation , 1995, Proceedings IEEE Conference on Industrial Automation and Control Emerging Technology Applications.

[18]  Ali K. Kamrani,et al.  A group technology based methodology for machine cell formation in a computer integrated manufacturing environment , 1993 .

[19]  John McAuley,et al.  Machine grouping for efficient production , 1972 .

[20]  K. Y. Tam,et al.  An operation sequence based similarity coefficient for part families formations , 1990 .