An Improved Fuzzy Clustering Method for Cellular Manufacturing

• Main Authors: LI, J., CHU, Chao-Hsien, WANG, Y., YAN, W.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2007
• Subjects: Cellular manufacturing; Cell formation; Fuzzy clustering; Fuzzy c-means; Computer Sciences; Operations Research, Systems Engineering and Industrial Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/1786; http://dx.doi.org/10.1080/00207540600634923
• Institution: Singapore Management University

Fuzzy c-means (FCM) has been successfully adapted to solve the manufacturing cell formation problem. However, when the problem becomes larger and especially if the data is ill structured, the FCM may result in clustering errors, infeasible solutions, and uneven distribution of parts/machines. In this paper, an improved fuzzy clustering algorithm is proposed to overcome the deficiencies of FCM. We tested the effects of algorithm parameters and compared its performance with the original and two popular FCM modifications. Our study shows that the proposed approach outperformed other alternatives. Most of the solutions it obtained are close to and in some cases better than the control solutions.