IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v34y2023i5d10.1007_s10845-022-01922-3.html
   My bibliography  Save this article

Digital twin-driven dynamic scheduling of a hybrid flow shop

Author

Listed:
  • Khalil Tliba

    (ISAE-SUPMECA
    Université de Tunis - ENSIT)

  • Thierno M. L. Diallo

    (ISAE-SUPMECA)

  • Olivia Penas

    (ISAE-SUPMECA)

  • Romdhane Ben Khalifa

    (Université de Tunis - ENSIT)

  • Noureddine Ben Yahia

    (Université de Tunis - ENSIT)

  • Jean-Yves Choley

    (ISAE-SUPMECA)

Abstract

Industries require, nowadays, to be more adaptable to unforeseen real-time events as well as to the rapid evolution of their market (e.g. multiplication of customers, increasingly personalized and unpredictable demand, etc.). To meet these challenges, manufacturers need new solutions to update their production plan when a change in the production system or its environment occurs. In this context, our research work deals with a dynamic scheduling problem of a real Hybrid Flow Shop considering the specific constraints of a perfume manufacturing company. This paper proposes a Digital Twin-driven dynamic scheduling approach based on the combination of both optimization and simulation. For the optimization, we have developed a mixed integer linear programming (MILP) scheduling model taking into account the main specific scheduling requirements of our case study. Regarding the simulation approach, a 3D shop floor model has been developed including the additional stochastic aspects and constraints which are difficult or impossible to model with a MILP approach. These two models are connected with the real shop floor to create a digital twin (DT). The developed DT allows the re-scheduling of production according to internal and external events. Finally, validation scenarios on a perfume case study have been designed and implemented in order to demonstrate the feasibility and the relevance of the proposed digital twin-driven dynamic scheduling approach.

Suggested Citation

  • Khalil Tliba & Thierno M. L. Diallo & Olivia Penas & Romdhane Ben Khalifa & Noureddine Ben Yahia & Jean-Yves Choley, 2023. "Digital twin-driven dynamic scheduling of a hybrid flow shop," Journal of Intelligent Manufacturing, Springer, vol. 34(5), pages 2281-2306, June.
    • Handle: RePEc:spr:joinma:v:34:y:2023:i:5:d:10.1007_s10845-022-01922-3
    DOI: 10.1007/s10845-022-01922-3
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-022-01922-3
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-022-01922-3?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. Kuo, Yiyo & Yang, Taho & Cho, Chiwoon & Tseng, Yao-Ching, 2008. "Using simulation and multi-criteria methods to provide robust solutions to dispatching problems in a flow shop with multiple processors," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(1), pages 40-56.
    2. Abedinnia, Hamid & Glock, C. H. & Schneider, Michael, 2017. "Machine scheduling in production: a content analysis," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 87242, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. Bennell, Julia A. & Mesgarpour, Mohammad & Potts, Chris N., 2017. "Dynamic scheduling of aircraft landings," European Journal of Operational Research, Elsevier, vol. 258(1), pages 315-327.
    4. Ruiz, Rubén & Vázquez-Rodríguez, José Antonio, 2010. "The hybrid flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 205(1), pages 1-18, August.
    5. Stephen C. Graves, 1981. "A Review of Production Scheduling," Operations Research, INFORMS, vol. 29(4), pages 646-675, August.
    6. Allahverdi, Ali & Gupta, Jatinder N. D. & Aldowaisan, Tariq, 1999. "A review of scheduling research involving setup considerations," Omega, Elsevier, vol. 27(2), pages 219-239, April.
    7. Lei Shi & Gang Guo & Xiaohui Song, 2021. "Multi-agent based dynamic scheduling optimisation of the sustainable hybrid flow shop in a ubiquitous environment," International Journal of Production Research, Taylor & Francis Journals, vol. 59(2), pages 576-597, January.
    8. Cowling, Peter & Johansson, Marcus, 2002. "Using real time information for effective dynamic scheduling," European Journal of Operational Research, Elsevier, vol. 139(2), pages 230-244, June.
    9. Suresh, V. & Chaudhuri, Dipak, 1993. "Dynamic scheduling--a survey of research," International Journal of Production Economics, Elsevier, vol. 32(1), pages 53-63, August.
    10. Janiak, Adam & Kozan, Erhan & Lichtenstein, Maciej & Oguz, Ceyda, 2007. "Metaheuristic approaches to the hybrid flow shop scheduling problem with a cost-related criterion," International Journal of Production Economics, Elsevier, vol. 105(2), pages 407-424, February.
    11. Kis, Tamas & Pesch, Erwin, 2005. "A review of exact solution methods for the non-preemptive multiprocessor flowshop problem," European Journal of Operational Research, Elsevier, vol. 164(3), pages 592-608, August.
    12. Leilei Meng & Chaoyong Zhang & Xinyu Shao & Biao Zhang & Yaping Ren & Wenwen Lin, 2020. "More MILP models for hybrid flow shop scheduling problem and its extended problems," International Journal of Production Research, Taylor & Francis Journals, vol. 58(13), pages 3905-3930, July.
    13. Muravev, Dmitri & Hu, Hao & Rakhmangulov, Aleksandr & Mishkurov, Pavel, 2021. "Multi-agent optimization of the intermodal terminal main parameters by using AnyLogic simulation platform: Case study on the Ningbo-Zhoushan Port," International Journal of Information Management, Elsevier, vol. 57(C).
    14. Brah, Shaukat A. & Hunsucker, John L., 1991. "Branch and bound algorithm for the flow shop with multiple processors," European Journal of Operational Research, Elsevier, vol. 51(1), pages 88-99, March.
    15. Victor Portougal & David J. Robb, 2000. "Production Scheduling Theory: Just Where Is It Applicable?," Interfaces, INFORMS, vol. 30(6), pages 64-76, December.
    16. Sirikarn Chansombat & Pupong Pongcharoen & Christian Hicks, 2019. "A mixed-integer linear programming model for integrated production and preventive maintenance scheduling in the capital goods industry," International Journal of Production Research, Taylor & Francis Journals, vol. 57(1), pages 61-82, January.
    17. Wei, Zelong & Song, Xi & Wang, Donghan, 2017. "Manufacturing flexibility, business model design, and firm performance," International Journal of Production Economics, Elsevier, vol. 193(C), pages 87-97.
    18. Romain Miclo & Matthieu Lauras & Franck Fontanili & Jacques Lamothe & Steven A. Melnyk, 2019. "Demand Driven MRP: assessment of a new approach to materials management," International Journal of Production Research, Taylor & Francis Journals, vol. 57(1), pages 166-181, January.
    Full references (including those not matched with items on IDEAS)

    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. Ruiz, Rubén & Vázquez-Rodríguez, José Antonio, 2010. "The hybrid flow shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 205(1), pages 1-18, August.
    2. Fátima Pilar & Eliana Costa e Silva & Ana Borges, 2023. "Optimizing Vehicle Repairs Scheduling Using Mixed Integer Linear Programming: A Case Study in the Portuguese Automobile Sector," Mathematics, MDPI, vol. 11(11), pages 1-23, June.
    3. Neufeld, Janis S. & Schulz, Sven & Buscher, Udo, 2023. "A systematic review of multi-objective hybrid flow shop scheduling," European Journal of Operational Research, Elsevier, vol. 309(1), pages 1-23.
    4. Quadt, Daniel & Kuhn, Heinrich, 2007. "Batch scheduling of jobs with identical process times on flexible flow lines," International Journal of Production Economics, Elsevier, vol. 105(2), pages 385-401, February.
    5. Chou, Fuh-Der, 2013. "Particle swarm optimization with cocktail decoding method for hybrid flow shop scheduling problems with multiprocessor tasks," International Journal of Production Economics, Elsevier, vol. 141(1), pages 137-145.
    6. Rossit, Daniel Alejandro & Tohmé, Fernando & Frutos, Mariano, 2018. "The Non-Permutation Flow-Shop scheduling problem: A literature review," Omega, Elsevier, vol. 77(C), pages 143-153.
    7. Ruiz, Ruben & Maroto, Concepcion, 2006. "A genetic algorithm for hybrid flowshops with sequence dependent setup times and machine eligibility," European Journal of Operational Research, Elsevier, vol. 169(3), pages 781-800, March.
    8. Weng, Wei & Fujimura, Shigeru, 2012. "Control methods for dynamic time-based manufacturing under customized product lead times," European Journal of Operational Research, Elsevier, vol. 218(1), pages 86-96.
    9. Figielska, Ewa, 2014. "A heuristic for scheduling in a two-stage hybrid flowshop with renewable resources shared among the stages," European Journal of Operational Research, Elsevier, vol. 236(2), pages 433-444.
    10. Nicolás Álvarez-Gil & Rafael Rosillo & David de la Fuente & Raúl Pino, 2021. "A discrete firefly algorithm for solving the flexible job-shop scheduling problem in a make-to-order manufacturing system," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(4), pages 1353-1374, December.
    11. Pan, Quan-Ke & Wang, Ling & Li, Jun-Qing & Duan, Jun-Hua, 2014. "A novel discrete artificial bee colony algorithm for the hybrid flowshop scheduling problem with makespan minimisation," Omega, Elsevier, vol. 45(C), pages 42-56.
    12. S. M. Mousavi & I. Mahdavi & J. Rezaeian & M. Zandieh, 2018. "An efficient bi-objective algorithm to solve re-entrant hybrid flow shop scheduling with learning effect and setup times," Operational Research, Springer, vol. 18(1), pages 123-158, April.
    13. Stef Moons & Katrien Ramaekers & An Caris & Yasemin Arda, 2018. "Integration of order picking and vehicle routing in a B2C e-commerce context," Flexible Services and Manufacturing Journal, Springer, vol. 30(4), pages 813-843, December.
    14. Fan Yang & Roel Leus, 2021. "Scheduling hybrid flow shops with time windows," Journal of Heuristics, Springer, vol. 27(1), pages 133-158, April.
    15. Mingxing Li & Ray Y. Zhong & Ting Qu & George Q. Huang, 2022. "Spatial–temporal out-of-order execution for advanced planning and scheduling in cyber-physical factories," Journal of Intelligent Manufacturing, Springer, vol. 33(5), pages 1355-1372, June.
    16. Luo, Hao & Du, Bing & Huang, George Q. & Chen, Huaping & Li, Xiaolin, 2013. "Hybrid flow shop scheduling considering machine electricity consumption cost," International Journal of Production Economics, Elsevier, vol. 146(2), pages 423-439.
    17. Chen, Yin-Yann & Cheng, Chen-Yang & Wang, Li-Chih & Chen, Tzu-Li, 2013. "A hybrid approach based on the variable neighborhood search and particle swarm optimization for parallel machine scheduling problems—A case study for solar cell industry," International Journal of Production Economics, Elsevier, vol. 141(1), pages 66-78.
    18. Quadt, Daniel & Kuhn, Heinrich, 2007. "A taxonomy of flexible flow line scheduling procedures," European Journal of Operational Research, Elsevier, vol. 178(3), pages 686-698, May.
    19. S. S. Panwalkar & Christos Koulamas, 2019. "The evolution of schematic representations of flow shop scheduling problems," Journal of Scheduling, Springer, vol. 22(4), pages 379-391, August.
    20. Missaoui, Ahmed & Ruiz, Rubén, 2022. "A parameter-Less iterated greedy method for the hybrid flowshop scheduling problem with setup times and due date windows," European Journal of Operational Research, Elsevier, vol. 303(1), pages 99-113.

    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:spr:joinma:v:34:y:2023:i:5:d:10.1007_s10845-022-01922-3. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.