Abstract
Cellular manufacturing emerged as a production strategy capable of finding sure issues of complexness and long manufacturing lead times in batch production. One of the major problems encountered in the development and implementation of cellular manufacturing is that of cell formation. The existing algorithm focuses on improving the grouping efficacy by reducing number of exceptional elements and voids. The lesser the number of exceptional elements and voids, the more efficient is the algorithm. The existing similarity coefficient method clustering algorithms are suffering from a common problem called chaining problem. In this paper, a new algorithm is proposed based on similarity coefficients for the cell formation. The proposed algorithm exhibits better results compared to existing algorithms by eliminating the chaining problem effectively. Grouping efficiency (η), grouping efficacy (μ), number of exceptional elements (EE), grouping index (γ) and grouping measure (\(\upeta_{g}\)) are the performance measures used for the analysis. KeywordsCellular manufacturingCell formationSimilarity coefficientChaining problem
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