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Optimisation of the Logistics System in an Electric Motor Assembly Flowshop by Integrating the Taguchi Approach and Discrete Event Simulation

Author

Listed:
  • Yongjian Jiang

    (College of Engineering, Zhejiang Normal University, No. 688 Yinbing Avenue, Jinhua 321004, China)

  • Dongyun Wang

    (College of Engineering, Zhejiang Normal University, No. 688 Yinbing Avenue, Jinhua 321004, China)

  • Wenjun Xia

    (College of Engineering, Zhejiang Normal University, No. 688 Yinbing Avenue, Jinhua 321004, China)

  • Wencai Li

    (Jinfei Holding Group Co., Ltd., Jinhua 321012, China)

Abstract

An electric motor assembly flowshop (EMAF) is a type of classical mixed-product assembly line that uses automatic guided vehicle (AGV) systems for material handling. To optimise the logistics system configuration and alleviate the impact of the AGV parameters on the efficiency of the EMAF, a modelling and optimisation method based on discrete event simulation (DES) combined with Taguchi orthogonal experimental design was proposed. A DES model of the entire production process for the EMAF was constructed using the Tecnomatix Plant Simulation software package. After optimisation of the principal layout in the DES model, the number of assembly stations was decreased from 13 to 9, and the balance ratio was increased from 65.08% to 84.65%. In addition, the combination of the Taguchi method with the DES model was further developed to achieve the optimal parameter combination of the AGVs in order to allow the AGVs to operate more efficiently under various states. The final overall theoretical throughput was increased from 134 to 295 units within the seven-hour observation period.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16770-:d:1003431
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    References listed on IDEAS

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    1. 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.
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    3. Kucukkoc, Ibrahim & Li, Zixiang & Karaoglan, Aslan D. & Zhang, David Z., 2018. "Balancing of mixed-model two-sided assembly lines with underground workstations: A mathematical model and ant colony optimization algorithm," International Journal of Production Economics, Elsevier, vol. 205(C), pages 228-243.
    4. 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.
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