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Multi-product scheduling through process mining: bridging optimization and machine process intelligence

Author

Listed:
  • Alexandre Checoli Choueiri

    (Pontifical Catholic University of Parana)

  • Eduardo Alves Portela Santos

    (Pontifical Catholic University of Parana)

Abstract

Small and medium enterprises (SMEs) may not have the maturity to put forward and unfold all the benefits from an ERP based system, a vital tool for production planning. Manufacturing ubiquitous trends, however, are more approachable to SMEs, and even the more affordable tools could be of great advantage. In this paper we propose an algorithmic framework that uses process mining tools to extract the underlying industrial process via Petri nets, and then retrieve all product tree necessary information to perform the multi-level scheduling. A faster solution decoding is proposed, for algorithms that uses random-keys. Computational experiments show that the new decoding is faster than the usual, leading to promising new paths on its future uses.

Suggested Citation

  • Alexandre Checoli Choueiri & Eduardo Alves Portela Santos, 2021. "Multi-product scheduling through process mining: bridging optimization and machine process intelligence," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1649-1667, August.
    • Handle: RePEc:spr:joinma:v:32:y:2021:i:6:d:10.1007_s10845-021-01767-2
    DOI: 10.1007/s10845-021-01767-2
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    References listed on IDEAS

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    1. Alexandre Moeuf & Robert Pellerin & Samir Lamouri & Simon Tamayo-Giraldo & Rodolphe Barbaray, 2018. "The industrial management of SMEs in the era of Industry 4.0," International Journal of Production Research, Taylor & Francis Journals, vol. 56(3), pages 1118-1136, February.
    2. Stadtler, Hartmut, 2011. "Multi-level single machine lot-sizing and scheduling with zero lead times," European Journal of Operational Research, Elsevier, vol. 209(3), pages 241-252, March.
    3. Chen, Kejia & Ji, Ping, 2007. "A mixed integer programming model for advanced planning and scheduling (APS)," European Journal of Operational Research, Elsevier, vol. 181(1), pages 515-522, August.
    4. X. Wang & S.K. Ong & A.Y.C. Nee, 2018. "A comprehensive survey of ubiquitous manufacturing research," International Journal of Production Research, Taylor & Francis Journals, vol. 56(1-2), pages 604-628, January.
    5. Pongcharoen, P. & Hicks, C. & Braiden, P. M. & Stewardson, D. J., 2002. "Determining optimum Genetic Algorithm parameters for scheduling the manufacturing and assembly of complex products," International Journal of Production Economics, Elsevier, vol. 78(3), pages 311-322, August.
    6. 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.
    7. James C. Bean, 1994. "Genetic Algorithms and Random Keys for Sequencing and Optimization," INFORMS Journal on Computing, INFORMS, vol. 6(2), pages 154-160, May.
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