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Integrated task sequence planning and assignment for human–robot collaborative assembly station

Author

Listed:
  • Yichen Wang

    (Huazhong University of Science and Technology)

  • Junfeng Wang

    (Huazhong University of Science and Technology)

  • Jindan Feng

    (Beijing Spacecrafts Limited Company)

  • Jinshan Liu

    (Beijing Spacecrafts Limited Company)

  • Xiaojun Liu

    (Southeast University)

Abstract

Human–robot collaborative assembly (HRCA) can give full play to their respective advantages and significantly improve assembly efficiency. Rational assembly sequences and task assignment schemes facilitate an efficient and smooth assembly process. This paper proposes a method of integrated assembly sequence planning and task assignment for HRCA based on the genetic algorithm (GA). Firstly, a part assembly process is decomposed into positioning task and connection task, which include a series of activities from the practical application aspect. Then, a dual-task precedence graph model for product assembly is accordingly constructed. Subsequently, GA is used to integrate assembly sequence planning and task assignment in HRCA considering time, complexity, and coherence as optimization objectives. By using Gantt charts, a chromosome encoding and decoding method based on human–robot collaborative assembly state diagrams in collaborative work is proposed to express assembly sequences and task assignment schemes. Finally, assembly process simulation is conducted to slightly adjust the assignment result considering potential collision in the shared time and space during HRCA. The case studies illustrate the feasibility and effectiveness of the proposed approach.

Suggested Citation

  • Yichen Wang & Junfeng Wang & Jindan Feng & Jinshan Liu & Xiaojun Liu, 2023. "Integrated task sequence planning and assignment for human–robot collaborative assembly station," Flexible Services and Manufacturing Journal, Springer, vol. 35(4), pages 979-1006, December.
    • Handle: RePEc:spr:flsman:v:35:y:2023:i:4:d:10.1007_s10696-022-09479-2
    DOI: 10.1007/s10696-022-09479-2
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    References listed on IDEAS

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    1. Parames Chutima, 2022. "A comprehensive review of robotic assembly line balancing problem," Journal of Intelligent Manufacturing, Springer, vol. 33(1), pages 1-34, January.
    2. Emilio Moretti & Elena Tappia & Martina Mauri & Marco Melacini, 2022. "A performance model for mobile robot-based part feeding systems to supermarkets," Flexible Services and Manufacturing Journal, Springer, vol. 34(3), pages 580-613, September.
    3. Yuxin Zhu & Dazuo Tian & Feng Yan, 2020. "Effectiveness of Entropy Weight Method in Decision-Making," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-5, March.
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