An improved fuzzy clustering method for cellular manufacturing

J. Li, C. H. Chu, Y. Wang, W. Yan

Research output: Contribution to journalArticle

21 Citations (Scopus)

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.

Original languageEnglish (US)
Pages (from-to)1049-1062
Number of pages14
JournalInternational Journal of Production Research
Volume45
Issue number5
DOIs
StatePublished - Mar 1 2007

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Cellular manufacturing
Fuzzy clustering
Machine components
Clustering algorithms

All Science Journal Classification (ASJC) codes

  • Strategy and Management
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

Cite this

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An improved fuzzy clustering method for cellular manufacturing. / Li, J.; Chu, C. H.; Wang, Y.; Yan, W.

In: International Journal of Production Research, Vol. 45, No. 5, 01.03.2007, p. 1049-1062.

Research output: Contribution to journalArticle

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