An integrated fuzzy DEA–fuzzy C-means–simulation for optimization of operator allocation in cellular manufacturing systems

This paper presents an integrated fuzzy data envelopment analysis (FDEA), fuzzy C-means and computer simulation for optimization of operator allocation in cellular manufacturing systems (CMS). This is a challenging issue in flexible manufacturing systems in general and in CMS in particular. A comput...

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Bibliographic Details
Published inInternational journal of advanced manufacturing technology Vol. 46; no. 1-4; pp. 361 - 375
Main Authors Azadeh, A., Anvari, M., Ziaei, B., Sadeghi, K.
Format Journal Article
LanguageEnglish
Published London Springer-Verlag 2010
Springer Nature B.V
Subjects
CAE) and Design
Cellular manufacture
Computer simulation
Computer-Aided Engineering (CAD
Data envelopment analysis
Decision making
Engineering
Flexible manufacturing systems
Fuzzy systems
Indicators
Industrial and Production Engineering
Manufacturing cells
Mechanical Engineering
Media Management
Multivariate analysis
Operations research
Optimization
Original Article
CMS
Integration
Fuzzy DEA
Operator allocation
Computer simulation
Fuzzy C-means
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Summary:This paper presents an integrated fuzzy data envelopment analysis (FDEA), fuzzy C-means and computer simulation for optimization of operator allocation in cellular manufacturing systems (CMS). This is a challenging issue in flexible manufacturing systems in general and in CMS in particular. A computer simulation model, which considers various operators layout, is developed. For considering more information from computer simulation report, the output data is fuzzified. FDEA is utilized to assess simulation alternatives in various levels of uncertainty. In addition, FDEA ranking of decision-making units are clustered by fuzzy C-means method. Each of the clusters indicates a degree of desirability for operator allocation. Previous studies only utilize multivariate analysis methods and simulation, whereas this study uses an integrated simulation, fuzzy DEA, fuzzy C-means, and fuzzy indicators. Furthermore, previous CMS studies consider only one type of product, whereas this study considers multiproduct for CMS modeling through simulation. Moreover, more robust CMS assessment indicators are used in the proposed model. A practical case study illustrates the effectiveness and superiority of the proposed methodology. In addition, we compared the results of U shape with other production types, namely spiral, straight, L, W, zigzag, and Z. Moreover, we show that it dominates the other production types.
ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-009-2088-6