PARALLEL FUZZY CLUSTERING OF PARTS AND MACHINES FOR CELLULAR MANUFACTURING

Cellular manufacturing attempts to identify concurrently part families requiring similar production processes and corresponding machine cells to manufacture those part families. Some authors have solved the problem using a fuzzy clustering approach based on the Fuzzy c-Means (FCM) algorithm. In this work we discuss the drawbacks of the application of FCM to this problem and we propose a new algorithm to overcome them. The modified FCM (MFCM) algorithm groups parts and machines concurrently and unlike FCM achieves a crisp assignment directly. We have also developed a computer program in order to test the comparative performance of MFCM, FCM and two heuristics (ZODIAC and GRAFICS) on a set of problems from the literature. MFCM outperforms the other methods although it requires longer computing times.