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Benefits of robust multiobjective optimization for flexible automotive assembly line balancing

Author

Listed:
  • Manuel Chica

    (The University of Newcastle)

  • Joaquín Bautista

    (Universitat Politcnica de Catalunya)

  • Jesica de Armas

    (Universitat Pompeu Fabra)

Abstract

Changing conditions and variations in the demand are frequent in real industrial environments. Decision makers have to take into account this uncertainty and manage it properly. One clear example is the automotive industry where manufacturers have to assume an uncertain and heterogeneous demand. For instance, automotive manufacturers must adapt their decisions when balancing the assembly line by considering different flexible solutions. Our proposal is using robust multiobjective optimization and simulation techniques to provide managers with a set of robust and equally-preferred solutions for assembly line balancing. We study a Nissan case where the demand of each product family is uncertain. The problem is addressed by considering a robust multiobjective model for assembly line balancing based on a high number of production plans. After the selection of six different assembly line configurations, we study the implications of robustness metrics based on workstations’ overload. We show that the adverse managerial effects of not having flexible line configuration when demand changes are alleviated. For the real Nissan automotive case, our analysis and conclusions show the managerial and industrial benefits of using robust assembly lines. We also encourage decision makers to use robust multiobjective optimization methods for selecting the most flexible decisions.

Suggested Citation

  • Manuel Chica & Joaquín Bautista & Jesica de Armas, 2019. "Benefits of robust multiobjective optimization for flexible automotive assembly line balancing," Flexible Services and Manufacturing Journal, Springer, vol. 31(1), pages 75-103, March.
    • Handle: RePEc:spr:flsman:v:31:y:2019:i:1:d:10.1007_s10696-018-9309-y
    DOI: 10.1007/s10696-018-9309-y
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    References listed on IDEAS

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    3. Sikora, Celso Gustavo Stall, 2024. "Balancing mixed-model assembly lines for random sequences," European Journal of Operational Research, Elsevier, vol. 314(2), pages 597-611.

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