MULTIPLE CRITERIA CLUSTERING-ALGORITHM FOR SOLVING THE GROUP TECHNOLOGY PROBLEM WITH MULTIPLE PROCESS ROUTINGS

This paper considers the machine-part clustering problem in group tech nology manufacturing in which for a part multiple process routings can be planned. Existing approaches using similarity coefficient to solve the problem suffer from computational burden which arises since;they use the similarity coefficients defined between routings of parts, not machines. Furthermore, existing methods do not deal effectively with the ill-structured problems in which mutually separable cells do not e xist. In this paper, we define the generalized machine similarity coef ficient. This approach saves considerable computer memory required to store the similarity coefficient information in comparison with the me thods using the similarity coefficients defined between parts. Further more, the new definition includes existing machine similarity coeffici ent as a special case. Unlike the existing algorithms using single clu stering criterion, a new algorithm using multiple clustering criteria is developed. The algorithm using the generalized machine similarity c oefficient effectively solves large-sized and ill-structured problems. Copyright (C) 1997 Elsevier Science Ltd