Serial 3D model reconstruction for machining evolution of rotational parts by merging semantic and graphic process planning information

  • Authors:

  • Shusheng Zhang;Yunfei Shi;Haitao Fan;Rui Huang;Julu Cao

  • Affiliations:

  • The Key Laboratory of Contemporary Designing and Integrated Manufacturing Technology, Ministry of Education of China, Northwestern Polytechnical University, 710072, Xi'an, PR China;The Key Laboratory of Contemporary Designing and Integrated Manufacturing Technology, Ministry of Education of China, Northwestern Polytechnical University, 710072, Xi'an, PR China;The Key Laboratory of Contemporary Designing and Integrated Manufacturing Technology, Ministry of Education of China, Northwestern Polytechnical University, 710072, Xi'an, PR China;The Key Laboratory of Contemporary Designing and Integrated Manufacturing Technology, Ministry of Education of China, Northwestern Polytechnical University, 710072, Xi'an, PR China;The Key Laboratory of Contemporary Designing and Integrated Manufacturing Technology, Ministry of Education of China, Northwestern Polytechnical University, 710072, Xi'an, PR China

  • Venue:
  • Computer-Aided Design
  • Year:
  • 2010

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Abstract

The manufacturing of a mechanical part is a dynamic evolution process from a raw workpiece to the final part, in which the generation of serial 3D models reflecting the changes on geometric shapes is especially critical to digital manufacturing. In this paper, an approach driven by the process planning course, the machining semantics and the machining geometry to reconstruct incrementally the serial 3D models for rotational part's dynamic evolution is proposed. The two major techniques involved are: (1) extraction of machining semantics based on process planning language understanding; (2) 3D reconstruction from 2D procedure working drawings guided by machining semantics and visualization for the reconstructed series of 3D models. Compared with the conventional 3D reconstruction methods, this approach introduced the process planning course and relevant information to implement a dynamic, incremental and knowledge-based reconstruction which can greatly reduce the efforts in reconstruction and extend the collection of geometric shapes to be reconstructed.