IDEAS home Printed from https://ideas.repec.org/a/spr/flsman/v34y2022i2d10.1007_s10696-021-09406-x.html
   My bibliography  Save this article

Robust scheduling and dispatching rules for high-mix collaborative manufacturing systems

Author

Listed:
  • Andrea Maria Zanchettin

    (Dipartimento di Elettronica, Informazione e Bioingegneria)

Abstract

Motivated by the increasing demand of mass customisation in production systems, this paper proposes a robust and adaptive scheduling and dispatching method for high-mix human-robot collaborative manufacturing facilities. Scheduling and dispatching rules are derived to optimally track the desired production within the mix, while handling uncertainty in job processing times. The sequencing policy is dynamically adjusted by online forecasting the throughput of the facility as a function of the scheduling and dispatching rules. Numerical verification experiments confirm the possibility to accurately track highly variable production requests, despite the uncertainty of the system.

Suggested Citation

  • Andrea Maria Zanchettin, 2022. "Robust scheduling and dispatching rules for high-mix collaborative manufacturing systems," Flexible Services and Manufacturing Journal, Springer, vol. 34(2), pages 293-316, June.
    • Handle: RePEc:spr:flsman:v:34:y:2022:i:2:d:10.1007_s10696-021-09406-x
    DOI: 10.1007/s10696-021-09406-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10696-021-09406-x
    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/s10696-021-09406-x?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. Paul Glasserman & David D. Yao, 1992. "Some Guidelines and Guarantees for Common Random Numbers," Management Science, INFORMS, vol. 38(6), pages 884-908, June.
    2. Jacek Blazewicz & Klaus H. Ecker & Erwin Pesch & Günter Schmidt & Malgorzata Sterna & Jan Weglarz, 2019. "Scheduling in Flexible Manufacturing Systems," International Handbooks on Information Systems, in: Handbook on Scheduling, edition 2, chapter 17, pages 671-711, Springer.
    3. Olivier Cardin & Damien Trentesaux & André Thomas & Pierre Castagna & Thierry Berger & Hind Bril El-Haouzi, 2017. "Coupling predictive scheduling and reactive control in manufacturing hybrid control architectures: state of the art and future challenges," Journal of Intelligent Manufacturing, Springer, vol. 28(7), pages 1503-1517, October.
    4. Ullah Saif & Zailin Guan & Li Zhang & Fei Zhang & Baoxi Wang & Jahanzaib Mirza, 2019. "Multi-objective artificial bee colony algorithm for order oriented simultaneous sequencing and balancing of multi-mixed model assembly line," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1195-1220, March.
    5. Jacek Blazewicz & Klaus H. Ecker & Erwin Pesch & Günter Schmidt & Malgorzata Sterna & Jan Weglarz, 2019. "Handbook on Scheduling," International Handbooks on Information Systems, Springer, edition 2, number 978-3-319-99849-7, November.
    6. K. C. Bhosale & P. J. Pawar, 2019. "Material flow optimisation of production planning and scheduling problem in flexible manufacturing system by real coded genetic algorithm (RCGA)," Flexible Services and Manufacturing Journal, Springer, vol. 31(2), pages 381-423, June.
    7. James T. Lin & Chun-Chih Chiu & Yu-Hsiang Chang, 2019. "Simulation-based optimization approach for simultaneous scheduling of vehicles and machines with processing time uncertainty in FMS," Flexible Services and Manufacturing Journal, Springer, vol. 31(1), pages 104-141, March.
    8. Dmitry Ivanov & Boris Sokolov & Weiwei Chen & Alexandre Dolgui & Frank Werner & Semyon Potryasaev, 2021. "A control approach to scheduling flexibly configurable jobs with dynamic structural-logical constraints," IISE Transactions, Taylor & Francis Journals, vol. 53(1), pages 21-38, 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. Sheldon H. Jacobson & Enver Yücesan, 1999. "On the Complexity of Verifying Structural Properties of Discrete Event Simulation Models," Operations Research, INFORMS, vol. 47(3), pages 476-481, June.
    2. Davide Mezzogori & Giovanni Romagnoli & Francesco Zammori, 2021. "Defining accurate delivery dates in make to order job-shops managed by workload control," Flexible Services and Manufacturing Journal, Springer, vol. 33(4), pages 956-991, December.
    3. Ivanov, Dmitry & Dolgui, Alexandre & Sokolov, Boris, 2022. "Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service”," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    4. Michael C. Fu & Jian-Qiang Hu & Chun-Hung Chen & Xiaoping Xiong, 2007. "Simulation Allocation for Determining the Best Design in the Presence of Correlated Sampling," INFORMS Journal on Computing, INFORMS, vol. 19(1), pages 101-111, February.
    5. Helmut A. Sedding, 2020. "Scheduling jobs with a V-shaped time-dependent processing time," Journal of Scheduling, Springer, vol. 23(6), pages 751-768, December.
    6. Hosseini, Amir & Otto, Alena & Pesch, Erwin, 2024. "Scheduling in manufacturing with transportation: Classification and solution techniques," European Journal of Operational Research, Elsevier, vol. 315(3), pages 821-843.
    7. N. Hilber & N. Reich & C. Schwab & C. Winter, 2009. "Numerical methods for Lévy processes," Finance and Stochastics, Springer, vol. 13(4), pages 471-500, September.
    8. Kaustav Kundu & Martin J. Land & Alberto Portioli-Staudacher & Jos A. C. Bokhorst, 2021. "Order review and release in make-to-order flow shops: analysis and design of new methods," Flexible Services and Manufacturing Journal, Springer, vol. 33(3), pages 750-782, September.
    9. Zixiang Li & Mukund Nilakantan Janardhanan & S. G. Ponnambalam, 2021. "Cost-oriented robotic assembly line balancing problem with setup times: multi-objective algorithms," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 989-1007, April.
    10. Pablo Alvarez-Campana & Felix Villafanez & Fernando Acebes & David Poza, 2024. "Simulation-based approach for Multiproject Scheduling based on composite priority rules," Papers 2406.02102, arXiv.org.
    11. Müller, David & Müller, Marcus G. & Kress, Dominik & Pesch, Erwin, 2022. "An algorithm selection approach for the flexible job shop scheduling problem: Choosing constraint programming solvers through machine learning," European Journal of Operational Research, Elsevier, vol. 302(3), pages 874-891.
    12. Briskorn, Dirk & Waldherr, Stefan, 2022. "Anarchy in the UJ: Coordination mechanisms for minimizing the number of late jobs," European Journal of Operational Research, Elsevier, vol. 301(3), pages 815-827.
    13. Adel Kacem & Abdelaziz Dammak, 2021. "Multi-objective scheduling on two dedicated processors," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(3), pages 694-721, October.
    14. Nowak, Maciek & Szufel, Przemysław, 2024. "Technician routing and scheduling for the sharing economy," European Journal of Operational Research, Elsevier, vol. 314(1), pages 15-31.
    15. Syed Abdul Rehman Khan & Muhammad Waqas & Xue Honggang & Naveed Ahmad & Zhang Yu, 2022. "Adoption of innovative strategies to mitigate supply chain disruption: COVID-19 pandemic," Operations Management Research, Springer, vol. 15(3), pages 1115-1133, December.
    16. Hasani, Ali & Hosseini, Seyed Mohammad Hassan, 2020. "A bi-objective flexible flow shop scheduling problem with machine-dependent processing stages: Trade-off between production costs and energy consumption," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    17. Nathan L. Kleinman & James C. Spall & Daniel Q. Naiman, 1999. "Simulation-Based Optimization with Stochastic Approximation Using Common Random Numbers," Management Science, INFORMS, vol. 45(11), pages 1570-1578, November.
    18. Boyle, Phelim & Broadie, Mark & Glasserman, Paul, 1997. "Monte Carlo methods for security pricing," Journal of Economic Dynamics and Control, Elsevier, vol. 21(8-9), pages 1267-1321, June.
    19. Mohd. Shaaban Hussain & Mohammed Ali, 2019. "A Multi-agent Based Dynamic Scheduling of Flexible Manufacturing Systems," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 20(3), pages 267-290, September.
    20. Sterna, Małgorzata, 2021. "Late and early work scheduling: A survey," Omega, Elsevier, vol. 104(C).

    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:flsman:v:34:y:2022:i:2:d:10.1007_s10696-021-09406-x. 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.