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

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Paul Glasserman & David D. Yao, 1992. "Some Guidelines and Guarantees for Common Random Numbers," Management Science, INFORMS, vol. 38(6), pages 884-908, June.
    8. 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.
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