IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v55y2017i13p3657-3673.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2016.1198506
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/00207543.2016.1198506?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. 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.
    3. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lamas, Patricio & Goycoolea, Marcos & Pagnoncelli, Bernardo & Newman, Alexandra, 2024. "A target-time-windows technique for project scheduling under uncertainty," European Journal of Operational Research, Elsevier, vol. 314(2), pages 792-806.
    2. 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.
    3. Akkan, Can & Erdem Külünk, M. & Koçaş, Cenk, 2016. "Finding robust timetables for project presentations of student teams," European Journal of Operational Research, Elsevier, vol. 249(2), pages 560-576.
    4. Öncü Hazir & Gündüz Ulusoy, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," Post-Print hal-02898162, HAL.
    5. Hazır, Öncü & Ulusoy, Gündüz, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," International Journal of Production Economics, Elsevier, vol. 223(C).
    6. Gislaine Mara Melega & Silvio Alexandre de Araujo & Reinaldo Morabito, 2020. "Mathematical model and solution approaches for integrated lot-sizing, scheduling and cutting stock problems," Annals of Operations Research, Springer, vol. 295(2), pages 695-736, December.
    7. Diaz, Juan Esteban & Handl, Julia & Xu, Dong-Ling, 2018. "Integrating meta-heuristics, simulation and exact techniques for production planning of a failure-prone manufacturing system," European Journal of Operational Research, Elsevier, vol. 266(3), pages 976-989.
    8. Juan, Angel A. & Faulin, Javier & Grasman, Scott E. & Rabe, Markus & Figueira, Gonçalo, 2015. "A review of simheuristics: Extending metaheuristics to deal with stochastic combinatorial optimization problems," Operations Research Perspectives, Elsevier, vol. 2(C), pages 62-72.
    9. Cambier, Adrien & Chardy, Matthieu & Figueiredo, Rosa & Ouorou, Adam & Poss, Michael, 2022. "Optimizing subscriber migrations for a telecommunication operator in uncertain context," European Journal of Operational Research, Elsevier, vol. 298(1), pages 308-321.
    10. Wolosewicz, Cathy & Dauzère-Pérès, Stéphane & Aggoune, Riad, 2015. "A Lagrangian heuristic for an integrated lot-sizing and fixed scheduling problem," European Journal of Operational Research, Elsevier, vol. 244(1), pages 3-12.
    11. Charles, Mehdi & Dauzère-Pérès, Stéphane & Kedad-Sidhoum, Safia & Mazhoud, Issam, 2022. "Motivations and analysis of the capacitated lot-sizing problem with setup times and minimum and maximum ending inventories," European Journal of Operational Research, Elsevier, vol. 302(1), pages 203-220.
    12. Sereshti, Narges & Adulyasak, Yossiri & Jans, Raf, 2024. "Managing flexibility in stochastic multi-level lot sizing problem with service level constraints," Omega, Elsevier, vol. 122(C).
    13. Sarhadi, Hassan & Naoum-Sawaya, Joe & Verma, Manish, 2020. "A robust optimization approach to locating and stockpiling marine oil-spill response facilities," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 141(C).
    14. Jeong, Jaehee & Premsankar, Gopika & Ghaddar, Bissan & Tarkoma, Sasu, 2024. "A robust optimization approach for placement of applications in edge computing considering latency uncertainty," Omega, Elsevier, vol. 126(C).
    15. Alexey Matveev & Varvara Feoktistova & Ksenia Bolshakova, 2016. "On Global Near Optimality of Special Periodic Protocols for Fluid Polling Systems with Setups," Journal of Optimization Theory and Applications, Springer, vol. 171(3), pages 1055-1070, December.
    16. Baker, Erin & Bosetti, Valentina & Salo, Ahti, 2016. "Finding Common Ground when Experts Disagree: Belief Dominance over Portfolios of Alternatives," MITP: Mitigation, Innovation and Transformation Pathways 243147, Fondazione Eni Enrico Mattei (FEEM).
    17. Qiu, Ruozhen & Sun, Minghe & Lim, Yun Fong, 2017. "Optimizing (s, S) policies for multi-period inventory models with demand distribution uncertainty: Robust dynamic programing approaches," European Journal of Operational Research, Elsevier, vol. 261(3), pages 880-892.
    18. Romauch, Martin & Hartl, Richard F., 2017. "Capacity planning for cluster tools in the semiconductor industry," International Journal of Production Economics, Elsevier, vol. 194(C), pages 167-180.
    19. Morteza Davari & Erik Demeulemeester, 2019. "The proactive and reactive resource-constrained project scheduling problem," Journal of Scheduling, Springer, vol. 22(2), pages 211-237, April.
    20. Melega, Gislaine Mara & de Araujo, Silvio Alexandre & Jans, Raf, 2018. "Classification and literature review of integrated lot-sizing and cutting stock problems," European Journal of Operational Research, Elsevier, vol. 271(1), pages 1-19.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:tprsxx:v:55:y:2017:i:13:p:3657-3673. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.