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Cellular manufacturing--A time-based analysis to the layout problem

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  • Angra, Surjit
  • Sehgal, Rakesh
  • Samsudeen Noori, Z.

Abstract

A cellular manufacturing system is an application of group technology principles to production. This involves processing groups of similar components in a dedicated cluster of dissimilar machines. In this paper, an approach that forms the cluster based on the processing time is suggested. For even distribution of workload, workload balancing is carried out in the second phase of the model, i.e., a time-based model. The time-based model is compared with the workload-based model using a commonality score. The performance of the time-based model is compared by means of workload deviation and deviation index. The validity of the approach is tested by application to the problems from the literature and the results are presented. The results indicate that the time-based model gives better even distribution of workload as compared to the workload-based model.

Suggested Citation

  • Angra, Surjit & Sehgal, Rakesh & Samsudeen Noori, Z., 2008. "Cellular manufacturing--A time-based analysis to the layout problem," International Journal of Production Economics, Elsevier, vol. 112(1), pages 427-438, March.
    • Handle: RePEc:eee:proeco:v:112:y:2008:i:1:p:427-438
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    References listed on IDEAS

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    1. Defersha, Fantahun M. & Chen, Mingyuan, 2006. "A comprehensive mathematical model for the design of cellular manufacturing systems," International Journal of Production Economics, Elsevier, vol. 103(2), pages 767-783, October.
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    5. Das, K. & Lashkari, R.S. & Sengupta, S., 2007. "Reliability consideration in the design and analysis of cellular manufacturing systems," International Journal of Production Economics, Elsevier, vol. 105(1), pages 243-262, January.
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    Cited by:

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    2. Koufteros, Xenophon & Lu, Guanyi & Peters, Richard C. & Lai, Kee-hung & Wong, Christina W.Y. & Edwin Cheng, T.C., 2014. "Product development practices, manufacturing practices, and performance: A mediational perspective," International Journal of Production Economics, Elsevier, vol. 156(C), pages 83-97.
    3. Mohd Fahmi Bin Mad Ali & Mohd Khairol Anuar Bin Mohd Ariffin & Faizal Bin Mustapha & Eris Elianddy Bin Supeni, 2021. "An Unsupervised Machine Learning-Based Framework for Transferring Local Factories into Supply Chain Networks," Mathematics, MDPI, vol. 9(23), pages 1-31, December.
    4. Hameri, Ari-Pekka, 2011. "Production flow analysis--Cases from manufacturing and service industry," International Journal of Production Economics, Elsevier, vol. 129(2), pages 233-241, February.
    5. Chandru Nagarajan Sathiyabama & Pramod Dasan, 2013. "Optimum Resource Allocation and Eliminating Waste Inside the Food Industry," Central European Business Review, Prague University of Economics and Business, vol. 2013(2), pages 31-44.

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