Symbolic clustering using a new dissimilarity measure
Pattern Recognition
A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
On statistically inference for fuzzy data with applications to descriptive statistics
Fuzzy Sets and Systems
On a class of fuzzy c-numbers clustering procedures for fuzzy data
Fuzzy Sets and Systems
Cell formation in group technology: review, evaluation and directions for future research
Computers and Industrial Engineering - Cellular manufacturing systems: design, analysis and implementation
Fuzzy clustering in cell formation with multiple attributes
Computers & Mathematics with Applications
Robust fuzzy clustering of relational data
IEEE Transactions on Fuzzy Systems
Computers and Operations Research
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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.