Hung, Wen-Liang; Yang, Miin-Shen; Lee, E. Stanley Cell formation using fuzzy relational clustering algorithm. (English) Zbl 1219.90058 Math. Comput. Modelling 53, No. 9-10, 1776-1787 (2011). Summary: Cellular manufacturing is a useful way to improve overall manufacturing performance. Group technology is used to increase the productivity for manufacturing high quality products and improving the flexibility of manufacturing systems. Cell formation is an important step in group technology. It is used in designing good cellular manufacturing systems. The key step in designing any cellular manufacturing system is the identification of part families and machine groups for the creation of cells that uses the similarities between parts in relation to the machines in their manufacture. There are two basic procedures for cell formation in group technology. One is part-family formation and the other is machine-cell formation. In this paper, we apply a fuzzy relational data clustering algorithm to form part families and machine groups. A real data study shows that the proposed approach performs well based on the grouping efficiency proposed by Chandrasekharan and Rajagopalan. MSC: 90B30 Production models 90C70 Fuzzy and other nonstochastic uncertainty mathematical programming Keywords:cellular manufacturing systems; cell formation; FRC algorithm; dissimilarity matrix; mixed-variable data Software:clusfind PDF BibTeX XML Cite \textit{W.-L. Hung} et al., Math. Comput. Modelling 53, No. 9--10, 1776--1787 (2011; Zbl 1219.90058) Full Text: DOI References: [1] Yin, Y.; Yasuda, K., Similarity coefficient methods applied to the cell formation problem: a taxonomy and review, International Journal of Production Economics, 101, 329-352 (2006) [2] Mosier, C. 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