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An assembly timing planning method based on knowledge and mixed integer linear programming

Author

Listed:
  • Jiahui Qian

    (Beijing Institute of Technology)

  • Zhijing Zhang

    (Beijing Institute of Technology)

  • Lingling Shi

    (Beijing Institute of Technology)

  • Dan Song

    (Beijing Institute of Technology)

Abstract

Assembly timing planning, which aims to solve the assembly action sequence and assembly part sequence with the shortest assembly time as the goal, is a necessary and critical step in intelligent assembly process planning. However, the current focus of assembly process planning is assembly sequence planning, whereas little research has been performed on assembly timing planning. A novel assembly timing planning method based on knowledge and mixed integer linear programming (MILP) is proposed in this paper. First, a knowledge base of the assembly process for timing planning is constructed using ontology. Then, based on the proposed strategy of dividing assembly timing planning into within-group planning and between-group planning, a MILP model of assembly timing planning for automatic assembly system is constructed. In addition, a software that realizes timing planning through human–machine collaboration is developed to verify and visualize the proposed timing planning method. The implementation is as follows: assembly action sentences are formed by searching the ontology keyword library, then timing knowledge for the action sequence and assembly sequence is established, and finally optimal assembly timing results are obtained after the calculation. Compared with the traditional serial assembly process, this method significantly reduces the assembly time, thereby improving the assembly efficiency, and the assembly schedule can be obtained automatically and quickly to guide the assembly process design.

Suggested Citation

  • Jiahui Qian & Zhijing Zhang & Lingling Shi & Dan Song, 2023. "An assembly timing planning method based on knowledge and mixed integer linear programming," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 429-453, February.
    • Handle: RePEc:spr:joinma:v:34:y:2023:i:2:d:10.1007_s10845-021-01819-7
    DOI: 10.1007/s10845-021-01819-7
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    References listed on IDEAS

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    1. Huang, Rong-Hwa & Yang, Chang-Lin, 2008. "Overlapping production scheduling planning with multiple objectives--An ant colony approach," International Journal of Production Economics, Elsevier, vol. 115(1), pages 163-170, September.
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