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Intelligent decision support system for flexible manufacturing system design

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  • Denis Borenstein

Abstract

The aim of this paper is to develop a new methodology of analysis and evaluation of Flexible Manufacturing System (FMS) design configurations. It examines the use of an integrated, systemic, global and user oriented approach for the complex problem of selecting among several configuration alternatives the most suitable for a specific case. The methodology is implemented using the Decision Support System framework, offering an objective tool to help managers and engineers during the design stage of the development cycle of these manufacturing systems. A case study illustrates the effectiveness of the developed methodology. Copyright Kluwer Academic Publishers 1998

Suggested Citation

  • Denis Borenstein, 1998. "Intelligent decision support system for flexible manufacturing system design," Annals of Operations Research, Springer, vol. 77(0), pages 129-156, January.
    • Handle: RePEc:spr:annopr:v:77:y:1998:i:0:p:129-156:10.1023/a:1018969126418
    DOI: 10.1023/A:1018969126418
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    Cited by:

    1. Manzini, Massimo & Unglert, Johannes & Gyulai, Dávid & Colledani, Marcello & Jauregui-Becker, Juan Manuel & Monostori, László & Urgo, Marcello, 2018. "An integrated framework for design, management and operation of reconfigurable assembly systems," Omega, Elsevier, vol. 78(C), pages 69-84.
    2. S.H.Sundarani & M. N. Qureshi, 2017. "Study Of Adoption Barriers For Flexible Manufacturing System In Industry," Working papers 2017-03-19, Voice of Research.
    3. Masoud Esmaeilikia & Behnam Fahimnia & Joeseph Sarkis & Kannan Govindan & Arun Kumar & John Mo, 2016. "Tactical supply chain planning models with inherent flexibility: definition and review," Annals of Operations Research, Springer, vol. 244(2), pages 407-427, September.
    4. Chan, Felix T. S. & Jiang, Bing & Tang, Nelson K. H., 2000. "The development of intelligent decision support tools to aid the design of flexible manufacturing systems," International Journal of Production Economics, Elsevier, vol. 65(1), pages 73-84, April.

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