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Process Planning, Scheduling, and Layout Optimization for Multi-Unit Mass-Customized Products in Sustainable Reconfigurable Manufacturing System

Author

Listed:
  • Sini Gao

    (Roberval (Mechanics, Energy and Electricity), Centre de Recherche Royallieu, Université de Technologie de Compiègne, CEDEX, CS 60319, 60203 Compiègne, France)

  • Joanna Daaboul

    (Roberval (Mechanics, Energy and Electricity), Centre de Recherche Royallieu, Université de Technologie de Compiègne, CEDEX, CS 60319, 60203 Compiègne, France)

  • Julien Le Duigou

    (Roberval (Mechanics, Energy and Electricity), Centre de Recherche Royallieu, Université de Technologie de Compiègne, CEDEX, CS 60319, 60203 Compiègne, France)

Abstract

Currently, manufacturers seek to provide customized and sustainable products, requiring flexible manufacturing systems and advanced production management to cope with customization complexity and improve environmental performance. The reconfigurable manufacturing system (RMS) is expected to provide cost-effective customization in high responsiveness. However, reconfiguration optimization to produce sustainable mass-customized products in RMS is a complex problem requiring multi-criteria decision making. It is related to three problems, process planning, scheduling, and layout optimization, which should be integrated to optimize the RMS performance. This paper aims at integrating the above three problems and developing an effective approach to solving them concurrently. It formulates a multi-objective mathematical model simultaneously optimizing process planning, job-shop scheduling, and open-field layout problem to improve RMS sustainability. The penalty for product tardiness, the total manufacturing cost, the hazardous waste, and the greenhouse gases emissions are minimized. Economic and environmental indicators are defined to modify the Pareto efficiency when searching the Pareto-optimal solutions. Exact Pareto-optimal solutions are obtained by brute-force search and compared with those of the non-environmental indicator model. NSGA-III is adopted to obtain the approximate Pareto-optimal solutions in high effectiveness and efficiency. A small numerical example is applied to validate the mathematical model and resolution methods.

Suggested Citation

  • Sini Gao & Joanna Daaboul & Julien Le Duigou, 2021. "Process Planning, Scheduling, and Layout Optimization for Multi-Unit Mass-Customized Products in Sustainable Reconfigurable Manufacturing System," Sustainability, MDPI, vol. 13(23), pages 1-24, December.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:23:p:13323-:d:692964
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    References listed on IDEAS

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    2. Da Silveira, Giovani & Borenstein, Denis & Fogliatto, Flavio S., 2001. "Mass customization: Literature review and research directions," International Journal of Production Economics, Elsevier, vol. 72(1), pages 1-13, June.
    3. Qi Wang & Peipei Qi & Shipei Li, 2021. "A Concurrence Optimization Model for Low-Carbon Product Family Design and the Procurement Plan of Components under Uncertainty," Sustainability, MDPI, vol. 13(19), pages 1-22, September.
    4. Kezia Amanda Kurniadi & Kwangyeol Ryu, 2021. "Development of Multi-Disciplinary Green-BOM to Maintain Sustainability in Reconfigurable Manufacturing Systems," Sustainability, MDPI, vol. 13(17), pages 1-19, August.
    5. Faycal A. Touzout & Lyes Benyoucef, 2019. "Multi-objective multi-unit process plan generation in a reconfigurable manufacturing environment: a comparative study of three hybrid metaheuristics," International Journal of Production Research, Taylor & Francis Journals, vol. 57(24), pages 7520-7535, December.
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