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Robust production planning and control for multi-stage systems with flexible final assembly lines

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  • Dávid Gyulai
  • András Pfeiffer
  • László Monostori

Abstract

Production planning of final assembly systems is a challenging task, as the often fluctuating order volumes require flexible solutions. Besides, the calculated plans need to be robust against the process-level disturbances and stochastic nature of some parameters like manual processing times or machine availability. In the paper, a simulation-based optimisation method is proposed that utilises lower level shop floor data to calculate robust production plans for final assembly lines of a flexible, multi-stage production system. In order to minimise the idle times when executing the plans, the capacity control that specifies the proper operator–task assignments is also determined. The analysed multi-stage system is operated with a pull strategy, which means that the production at the final assembly lines generates demands for the preceding stages providing the assembled components. In order to guarantee the feasibility of the plans calculated for the final assembly lines, a decomposition approach is proposed to optimise the production plan of preceding stages. By this way, the robust production can be ensured resulting in reduced losses and overall production costs even though the system is exposed to changes and disturbances.

Suggested Citation

  • Dávid Gyulai & András Pfeiffer & László Monostori, 2017. "Robust production planning and control for multi-stage systems with flexible final assembly lines," International Journal of Production Research, Taylor & Francis Journals, vol. 55(13), pages 3657-3673, July.
  • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:13:p:3657-3673
    DOI: 10.1080/00207543.2016.1198506
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    References listed on IDEAS

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    1. Almeder, Christian & Klabjan, Diego & Traxler, Renate & Almada-Lobo, Bernardo, 2015. "Lead time considerations for the multi-level capacitated lot-sizing problem," European Journal of Operational Research, Elsevier, vol. 241(3), pages 727-738.
    2. Gabrel, Virginie & Murat, Cécile & Thiele, Aurélie, 2014. "Recent advances in robust optimization: An overview," European Journal of Operational Research, Elsevier, vol. 235(3), pages 471-483.
    3. Melouk, Sharif H. & Freeman, Nickolas K. & Miller, David & Dunning, Michelle, 2013. "Simulation optimization-based decision support tool for steel manufacturing," International Journal of Production Economics, Elsevier, vol. 141(1), pages 269-276.
    4. Helber, Stefan & Sahling, Florian, 2010. "A fix-and-optimize approach for the multi-level capacitated lot sizing problem," International Journal of Production Economics, Elsevier, vol. 123(2), pages 247-256, February.
    5. Gansterer, Margaretha & Almeder, Christian & Hartl, Richard F., 2014. "Simulation-based optimization methods for setting production planning parameters," International Journal of Production Economics, Elsevier, vol. 151(C), pages 206-213.
    6. Aytug, Haldun & Lawley, Mark A. & McKay, Kenneth & Mohan, Shantha & Uzsoy, Reha, 2005. "Executing production schedules in the face of uncertainties: A review and some future directions," European Journal of Operational Research, Elsevier, vol. 161(1), pages 86-110, February.
    7. Byrne, M.D. & Hossain, M.M., 2005. "Production planning: An improved hybrid approach," International Journal of Production Economics, Elsevier, vol. 93(1), pages 225-229, January.
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    Cited by:

    1. Hadi Farhangi, 2021. "Multi-Echelon Supply Chains with Lead Times and Uncertain Demands," SN Operations Research Forum, Springer, vol. 2(3), pages 1-25, September.
    2. Boby John & Rajeshwar S. Kadadevaramath, 2019. "Optimization of software development life cycle process to minimize the delivered defect density," OPSEARCH, Springer;Operational Research Society of India, vol. 56(4), pages 1199-1212, December.
    3. Anderson Hoose & Víctor Yepes & Moacir Kripka, 2021. "Selection of Production Mix in the Agricultural Machinery Industry Considering Sustainability in Decision Making," Sustainability, MDPI, vol. 13(16), pages 1-14, August.

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