An Improved Fuzzy Clustering Method for Cellular Manufacturing

Publication Type

Journal Article

Publication Date

2007

Abstract

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.

Keywords

Cellular manufacturing, Cell formation, Fuzzy clustering, Fuzzy c-means

Discipline

Computer Sciences | Operations Research, Systems Engineering and Industrial Engineering

Research Areas

Information Systems and Management

Publication

International Journal of Production Research

Volume

45

Issue

5

First Page

1049

Last Page

1062

ISSN

0020-7543

Identifier

10.1080/00207540600634923

Publisher

Taylor and Francis

Additional URL

http://dx.doi.org/10.1080/00207540600634923

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