A fuzzy analysis approach for part-machine grouping in cellular manufacturing systems

Abstract

Among the many accepted clustering techniques, the fuzzy clustering approaches have been developed over the last decades. These approaches have been applied to many areas in manufacturing systems. In this paper, a fuzzy clustering approach is proposed for selecting machine cells and part families in cellular manufacturing systems. This fuzzy approach offers a special advantage over existing clustering approaches as it presents the degree of membership of the machine or part associated with each machine cell or part family allowing users flexibility in formulating machine cells and part families. The proposed algorithm is extended and validated using numerical examples to demonstrate its application in cellular manufacturing.