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Sequential graph-based routing algorithm for electrical harnesses, tubes, and hoses in a commercial vehicle

Author

Listed:
  • Saekyeol Kim

    (Hanyang University)

  • Taehyeok Choi

    (Hanyang University)

  • Shinyu Kim

    (Hanyang University)

  • Taejoon Kwon

    (Hanyang University)

  • Tae Hee Lee

    (Hanyang University)

  • Kwangrae Lee

    (Hyundai Motor Company)

Abstract

The routing design of the various electrical wires, tubes, and hoses of a commercial vehicle requires a significant number of man-hours because of the variety of the commercial vehicles, frequent design changes of other vehicular components and the manual trial-and-error approaches. This study proposes a new graph-based routing algorithm to find the collision-free routing path in the constrained space of a commercial vehicle. Minimal spanning tree is adopted to connect multi-terminal points in a graph and Dijkstra’s algorithm is used to find the shortest route among the candidate paths; the design domain is divided into several sub-domains to simplify the graph and the proposed algorithm solves the routing problems in a sequential manner to deal intermediate points. Then, the proposed method was applied to the design of the routes for four different routing components of a commercial truck. The results indicate that the developed methodology can provide a satisfactory routing design satisfying all the requirements of the design experts in the automotive industry.

Suggested Citation

  • Saekyeol Kim & Taehyeok Choi & Shinyu Kim & Taejoon Kwon & Tae Hee Lee & Kwangrae Lee, 2021. "Sequential graph-based routing algorithm for electrical harnesses, tubes, and hoses in a commercial vehicle," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 917-933, April.
    • Handle: RePEc:spr:joinma:v:32:y:2021:i:4:d:10.1007_s10845-020-01596-9
    DOI: 10.1007/s10845-020-01596-9
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    References listed on IDEAS

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    1. Yanfeng Qu & Dan Jiang & Qingyan Yang, 2018. "Branch pipe routing based on 3D connection graph and concurrent ant colony optimization algorithm," Journal of Intelligent Manufacturing, Springer, vol. 29(7), pages 1647-1657, October.
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    Cited by:

    1. Xinjian Deng & Jianhua Liu & Hao Gong & Jiayu Huang, 2023. "A novel vision-based method for loosening detection of marked T-junction pipe fittings integrating GAN-based segmentation and SVM-based classification algorithms," Journal of Intelligent Manufacturing, Springer, vol. 34(6), pages 2581-2597, August.

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    1. Xinjian Deng & Jianhua Liu & Hao Gong & Jiayu Huang, 2023. "A novel vision-based method for loosening detection of marked T-junction pipe fittings integrating GAN-based segmentation and SVM-based classification algorithms," Journal of Intelligent Manufacturing, Springer, vol. 34(6), pages 2581-2597, August.

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