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Journal of Graphics ›› 2024, Vol. 45 ›› Issue (3): 564-574.DOI: 10.11996/JG.j.2095-302X.2024030564

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Research on drive axle assembly sequence planning based on semantic process knowledge

WANG Gangfeng1(), ZHANG Huan1, LIU Simeng1(), YUE Ping2, ZHANG Dong1   

  1. 1. Key Laboratory of Road Construction Technology and Equipment of MOE, Chang'an University, Xi'an Shaanxi 710064, China
    2. State Sida Machinery Manufacturing Company, Xianyang Shaanxi 712200, China
  • Received:2023-10-10 Accepted:2024-01-25 Online:2024-06-30 Published:2024-06-12
  • Contact: LIU Simeng (1988-), engineer, Ph.D. Her main research interests cover advanced manufacturing technology, CAD/CAM. E-mail:liusimeng@chd.edu.cn
  • About author:

    WANG Gangfeng (1983-), senior engineer, Ph.D. His main research interests cover digital design and manufacturing, intelligent construction machinery. E-mail:wanggf@chd.edu.cn

  • Supported by:
    Natural Science Basic Research Project of Shaanxi Province(2019JM-073);Natural Science Basic Research Project of Shaanxi Province(2022JQ-515);Educational Scientific Planning Project of the 14th Five-Year Plan of Shaanxi Province(SGH22Y1274);Collaborative Education Project of Industry-University Cooperation of the Ministry of Education(230802436213147)

Abstract:

In response to the lack of knowledge-based reasoning and decision-making in the assembly sequence planning of construction machinery drive axles, which makes it difficult to realize intelligent assembly of complex products, a method for assembly sequence planning based on semantic process knowledge was proposed. The semantic process knowledge information model of the drive axle assembly was constructed to express the hierarchical structure information, attribute information, and assembly semantic information of sub-assemblies. By establishing an assembly sequence planning ontology and introducing semantics web rule language (SWRL) rules into the assembly ontology, the semantic representation and reasoning and decision-making of process knowledge were studied. The process knowledge graph of the drive axle was constructed using Neo4j, and the assembly sequence of typical structural sub-assemblies was quickly identified. By quantifying the influence of geometric properties, physical properties, and assembly process information of parts on assembly efficiency, the assembly weight sequence was generated, and the assembly sequence of atypical structure sub-assemblies was iteratively modified by SWRL rules. Finally, the feasibility of the proposed method was verified by generating and simulating the assembly sequence of the drive axle of a certain model of road roller, providing a reference for knowledge-driven complex product assembly sequence planning.

Key words: assembly sequence planning, drive axle, ontology modeling, rule-based reasoning, knowledge graph

CLC Number: