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A self-organized approach for scheduling semiconductor manufacturing systems

Author

Listed:
  • Qingyun Yu

    (Tongji University)

  • Haolin Yang

    (Tongji University)

  • Kuo-Yi Lin

    (Tongji University
    Tongji University)

  • Li Li

    (Tongji University
    Tongji University)

Abstract

In semiconductor manufacturing industry, traditional scheduling rules are not conducive to improving production capacity to autonomously adjust based on real-time status. To fill this gap, this study proposes a dynamic dispatching rule based on self-organization (DDRSO) to autogenerate optimal scheduling scheme through mechanisms of interaction, coordination and competition. Besides, an extended DDRSO is proposed to further consider hot lots and transient dynamic bottlenecks. Both DDRSO and E-DDRSO are designed from three aspects: role definition of self-organization units, negotiation mechanism among self-organization units, and decision methods. This research adopts a benchmark industrial manufacturing system to illustrate the availability of the proposed approach. Compared with heuristic dispatching strategies, DDRSO achieves improvement on MOV, TH and ODR by 4.9%, 9.06% and 20.23%, respectively. Meanwhile, E-DDRSO performs better than DDRSO under all workload levels. In addition, compared with a flexible dispatching method BPSO-SVM, E-DDRSO also obtain better performances, especially improvement on CT by 16.51%.

Suggested Citation

  • Qingyun Yu & Haolin Yang & Kuo-Yi Lin & Li Li, 2021. "A self-organized approach for scheduling semiconductor manufacturing systems," Journal of Intelligent Manufacturing, Springer, vol. 32(3), pages 689-706, March.
    • Handle: RePEc:spr:joinma:v:32:y:2021:i:3:d:10.1007_s10845-020-01678-8
    DOI: 10.1007/s10845-020-01678-8
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    References listed on IDEAS

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    1. Tsui-Ping Chung & Zhen Xue & Tong Wu & Stephen C. Shih, 2019. "Minimising total completion time on single-machine scheduling with new integrated maintenance activities," International Journal of Production Research, Taylor & Francis Journals, vol. 57(3), pages 918-930, February.
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    4. Peng Zhang & Youlong Lv & Jie Zhang, 2018. "An improved imperialist competitive algorithm based photolithography machines scheduling," International Journal of Production Research, Taylor & Francis Journals, vol. 56(3), pages 1017-1029, February.
    5. Fei Shi & Shikui Zhao & Yue Meng, 2020. "Hybrid algorithm based on improved extended shifting bottleneck procedure and GA for assembly job shop scheduling problem," International Journal of Production Research, Taylor & Francis Journals, vol. 58(9), pages 2604-2625, May.
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    Cited by:

    1. Jianxin Fang & Brenda Cheang & Andrew Lim, 2023. "Problems and Solution Methods of Machine Scheduling in Semiconductor Manufacturing Operations: A Survey," Sustainability, MDPI, vol. 15(17), pages 1-44, August.
    2. Yongjian Jiang & Dongyun Wang & Wenjun Xia & Wencai Li, 2022. "Optimisation of the Logistics System in an Electric Motor Assembly Flowshop by Integrating the Taguchi Approach and Discrete Event Simulation," Sustainability, MDPI, vol. 14(24), pages 1-15, December.

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