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Fuzzy multi-criteria decision model for evaluating reconfigurable machines

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  • Abdi, M.R.

Abstract

The design and configuration of manufacturing equipment require crucial decision considering optimum capacity and functionality. The equipment selection problem might be involved with choosing between large-capacity machines versus a greater number of machines with smaller capacities, and/or dedicated facilities versus multi-product facilities. This paper investigates reconfigurable machining system characteristics in order to identify the crucial factors influencing the machine selection and the machine (re)configuration. Furthermore, changeover cost and changeover time while switching from one product to the other are taken into account. In particular, a fuzzy analytical hierarchical process (FAHP) model is proposed to integrate the decisive factors for the equipment selection process under uncertainty. The expected values of the normalised fuzzy sets are determined to identify the preference values of the alternative machines. The fuzzy multi-criteria model is analysed within the fuzzy domains of the operational characteristics along with economic, quality and performance criteria. The proposed model is examined using monitoring sensitivity analysis through a case study. As a result, the alternative machines are prioritised with consideration of the inconsistency ratios. The relative performances of the alternative equipment in view of interactions of process reconfigurability and cost, and capacity and functionality are graphically illustrated.

Suggested Citation

  • Abdi, M.R., 2009. "Fuzzy multi-criteria decision model for evaluating reconfigurable machines," International Journal of Production Economics, Elsevier, vol. 117(1), pages 1-15, January.
    • Handle: RePEc:eee:proeco:v:117:y:2009:i:1:p:1-15
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    Cited by:

    1. Ateekh Ur Rehman & Syed Hammad Mian & Usama Umer & Yusuf Siraj Usmani, 2019. "Strategic Outcome Using Fuzzy-AHP-Based Decision Approach for Sustainable Manufacturing," Sustainability, MDPI, vol. 11(21), pages 1-22, October.
    2. Ortega-Jimenez, Cesar H. & Garrido-Vega, Pedro & Cruz Torres, Cristian Andrés, 2020. "Achieving plant responsiveness from reconfigurable technology: Intervening role of SCM," International Journal of Production Economics, Elsevier, vol. 219(C), pages 195-203.
    3. Xia, Tangbin & Xi, Lifeng & Pan, Ershun & Ni, Jun, 2017. "Reconfiguration-oriented opportunistic maintenance policy for reconfigurable manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 87-98.
    4. Ortega Jimenez, Cesar H. & Machuca, Jose A.D. & Garrido-Vega, Pedro & Filippini, Roberto, 2015. "The pursuit of responsiveness in production environments: From flexibility to reconfigurability," International Journal of Production Economics, Elsevier, vol. 163(C), pages 157-172.
    5. Baykasoglu, Adil & ÖzbakIr, Lale, 2010. "Analyzing the effect of dispatching rules on the scheduling performance through grammar based flexible scheduling system," International Journal of Production Economics, Elsevier, vol. 124(2), pages 369-381, April.
    6. Wang, Xiaojun & Chan, Hing Kai & Yee, Rachel W.Y. & Diaz-Rainey, Ivan, 2012. "A two-stage fuzzy-AHP model for risk assessment of implementing green initiatives in the fashion supply chain," International Journal of Production Economics, Elsevier, vol. 135(2), pages 595-606.
    7. L. A. Shah & A. Etienne & A. Siadat & F. Vernadat, 2016. "Decision-making in the manufacturing environment using a value-risk graph," Journal of Intelligent Manufacturing, Springer, vol. 27(3), pages 617-630, June.
    8. Wong, Bo K. & Lai, Vincent S., 2011. "A survey of the application of fuzzy set theory in production and operations management: 1998-2009," International Journal of Production Economics, Elsevier, vol. 129(1), pages 157-168, January.
    9. Battaïa, Olga & Dolgui, Alexandre & Guschinsky, Nikolai, 2023. "MIP-based heuristics for combinatorial design of reconfigurable rotary transfer machines for production of multiple parts," International Journal of Production Economics, Elsevier, vol. 262(C).
    10. Vinod, V. & Sridharan, R., 2011. "Simulation modeling and analysis of due-date assignment methods and scheduling decision rules in a dynamic job shop production system," International Journal of Production Economics, Elsevier, vol. 129(1), pages 127-146, January.

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