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Rule and branch-and-bound algorithm based sequencing of machining features for process planning of complex parts

Author

Listed:
  • Wei Wang

    (Nanjing University of Aeronautics and Astronautics)

  • Yingguang Li

    (Nanjing University of Aeronautics and Astronautics)

  • Lingling Huang

    (Nanjing University of Aeronautics and Astronautics)

Abstract

The machining sequence of machining features is vital to achieve efficient and high quality manufacturing of complex NC machining parts. In most feature-based process planning system, the machining features are sequenced as the lowest level unit. However, a single machining feature of complex parts such as aircraft structural parts is usually machined by multiple machining operations. The one-to-many mappings between the machining features and the machining operations cause the increase of the non-cutting tool path. In order to solve this problem, some types of machining features of complex parts are decomposed into several sub-machining features that are associated with a single machining operation individually according to the rules which are abstracted from the machining process of complex parts. Benefitting from the decomposition, the sub-machining features from different machining feature can be assembled into a sub-machining feature in order to avoid the cutting tool marks. The different types of sub-machining features are sequenced in the light of some rules which are also extracted from the machining process of complex parts. And the branch-and-bound algorithm are employed to sequence the same type sub-machining features to minimum the non-cutting tool path. A pilot feature-based process planning system has been developed based on this research, and has been used in some aircraft manufacturers in China.

Suggested Citation

  • Wei Wang & Yingguang Li & Lingling Huang, 2018. "Rule and branch-and-bound algorithm based sequencing of machining features for process planning of complex parts," Journal of Intelligent Manufacturing, Springer, vol. 29(6), pages 1329-1336, August.
    • Handle: RePEc:spr:joinma:v:29:y:2018:i:6:d:10.1007_s10845-015-1181-y
    DOI: 10.1007/s10845-015-1181-y
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    Cited by:

    1. Qihao Liu & Xinyu Li & Liang Gao, 2021. "Mathematical modeling and a hybrid evolutionary algorithm for process planning," Journal of Intelligent Manufacturing, Springer, vol. 32(3), pages 781-797, March.
    2. G. Cherif & E. Leclercq & D. Lefebvre, 2023. "Scheduling of a class of partial routing FMS in uncertain environments with beam search," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 493-514, February.

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