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Cell design and multi-period machine loading in cellular reconfigurable manufacturing systems with alternative routing

Author

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  • Ignacio Eguia
  • Jose Carlos Molina
  • Sebastian Lozano
  • Jesus Racero

Abstract

This paper deals with the design and loading of Cellular Reconfigurable Manufacturing Systems in the presence of alternative routing and multiple time periods. These systems consist of multiple reconfigurable machining cells, each of which has Reconfigurable Machine Tools and Computer Numerical Control (CNC) machines. Each reconfigurable machine has a library of feasible auxiliary machine modules for achieving particular operational capabilities, while each CNC machine has an automatic tool changer and a tool magazine of a limited capacity. The proposed approach consists of two phases: the machine cell design phase which involves the grouping of machines into machine cells, and the cell loading phase that determines the routing mix and the tool and module allocation. In this paper, the cell design problem is modelled as an Integer Linear Programming formulation, considering the multiple process plans of each part type as if they were separate part types. Once the manufacturing cells are formed, a Mixed Integer Linear Programming model is developed for the cell loading problem, considering multi-period demands for the part types, and minimising transportation and holding costs while keeping the machine and cell utilisations in each period, and the system utilisation across periods, approximately balanced. An illustrative problem and experimental results are presented.

Suggested Citation

  • Ignacio Eguia & Jose Carlos Molina & Sebastian Lozano & Jesus Racero, 2017. "Cell design and multi-period machine loading in cellular reconfigurable manufacturing systems with alternative routing," International Journal of Production Research, Taylor & Francis Journals, vol. 55(10), pages 2775-2790, May.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:10:p:2775-2790
    DOI: 10.1080/00207543.2016.1193673
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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. Ma, Yujie & Du, Gang & Jiao, Roger J., 2020. "Optimal crowdsourcing contracting for reconfigurable process planning in open manufacturing: A bilevel coordinated optimization approach," International Journal of Production Economics, Elsevier, vol. 228(C).
    3. Feng, Yanling & Li, Guo & Sethi, Suresh P., 2018. "A three-layer chromosome genetic algorithm for multi-cell scheduling with flexible routes and machine sharing," International Journal of Production Economics, Elsevier, vol. 196(C), pages 269-283.
    4. Iqbal, Asif & Al-Ghamdi, Khalid A., 2018. "Energy-efficient cellular manufacturing system: Eco-friendly revamping of machine shop configuration," Energy, Elsevier, vol. 163(C), pages 863-872.

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