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Towards a sustainable reconfigurable manufacturing system (SRMS): multi-objective based approaches for process plan generation problem

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  • Amirhossein Khezri
  • Hichem Haddou Benderbal
  • Lyes Benyoucef

Abstract

Nowadays to meet the continuously growing worldwide demand for capital and consumer goods while considering the associated economic, environmental, and social aspects, new generation of manufacturing systems are developed and adopted. The goal is to respond to changing market needs while minimising adverse effects on the environment. Reconfigurable manufacturing system (RMS) – due to its flexibility and characteristics – can increase the system sustainability and responsiveness to satisfy the market needs. This paper considers an environmental oriented multi-objective process plan generation problem for a sustainable reconfigurable manufacturing system (SRMS). Three criteria are minimised respectively the sustainability-metric value, the total production time and the total production cost. As a new criterion, the sustainability-metric value considers both liquid hazardous waste and greenhouse gas emissions (GHG). First, a multi-objective integer linear programming (MOILP) model is proposed. Second, due to the problem complexity, three approaches are adapted respectively a posteriori approach called augmented ε-constraint (AUGECON) and two evolutionary approaches namely, non-dominated sorting genetic algorithm II (NSGA-II) and strength Pareto evolutionary algorithm II (SPEA-II). Finally, due to the lack of real world data and to illustrate the applicability of the three approaches, a simple numerical example is presented and the obtained numerical results are analysed.

Suggested Citation

  • Amirhossein Khezri & Hichem Haddou Benderbal & Lyes Benyoucef, 2021. "Towards a sustainable reconfigurable manufacturing system (SRMS): multi-objective based approaches for process plan generation problem," International Journal of Production Research, Taylor & Francis Journals, vol. 59(15), pages 4533-4558, August.
  • Handle: RePEc:taf:tprsxx:v:59:y:2021:i:15:p:4533-4558
    DOI: 10.1080/00207543.2020.1766719
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    Cited by:

    1. Hao, Xinye & Zheng, Li & Li, Na & Zhang, Canrong, 2022. "Integrated bin packing and lot-sizing problem considering the configuration-dependent bin packing process," European Journal of Operational Research, Elsevier, vol. 303(2), pages 581-592.
    2. 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).

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