Fuzzy clustering in cell formation with multiple attributes

Authors:
G. Naadimuthu;P. Gultom;E. S. Lee
Affiliations:
Department of Information Systems and Decision Sciences, Silberman College of Business, Fairleigh Dickinson University, Madison, NJ 07940, USA;Department of Industrial and Manufacturing Systems Engineering, Kansas State University, Manhattan, KS 66506, USA;Department of Industrial and Manufacturing Systems Engineering, Kansas State University, Manhattan, KS 66506, USA
Venue:
Computers & Mathematics with Applications
Year:
2010

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Abstract

An approach based on fuzzy clustering and aggregation operators is proposed to design cell formation involving multiple criteria or multiple attributes. The three most basic attributes in cell formation, namely, number of machines required, processing time, and common tools required on machines, are considered. The results are compared with the single attribute results of Chu and Hayya (1991) [27].