Integrating part modeling and assembly modeling from the perspective of process
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Part modeling and assembly modeling are two important aspects of product modeling, which is crucial to manufacturing industrial completeness. Although the two aspects are greatly integrated, they are separated at the process level in current CAD systems. As a result, the design intent expressed at part modeling stage has to be expressed again at assembly modeling stage, through tedious and error-prone manual selection of geometric entities and assignment of mating constraints. To alleviate the problems, an approach to integrate part modeling and assembly modeling from the perspective of process is proposed. In this method, the previously developed concept of assembly feature pair (AFP), and the recently generalized and formalized phenomenon of structure pre-mapping (SPM) are introduced; AFP can be constructed in a mathematical way, and is utilized to describe the design intent existed in designers’ brain systematically; SPM is realized by associating AFPs into part solid models; in this way, the design intent is stored in part solid models at part modeling stage, thus bridging the gaps between part modeling and assembly modeling at process level, and providing heuristics for assembly modeling automation. On this basis, the natural relationships between part modeling and assembly modeling at process level are revealed, paving the way to formalize part modeling and assembly modeling from the perspective of process in a unified framework. Finally, an implementation sample is demonstrated to validate the feasibility of the proposed approach. The proposed integration theoretical system at process level may provide the potential to facilitate the paradigm shift in product modeling to make it simpler and integrate more downstream applications.
KeywordsPart modeling Assembly modeling Integration of process Design intent description Structure pre-mapping Assembly feature pair
This work is financially supported by Nature Science Foundation of China (51505152, 51275177), the China Postdoctoral Science Foundation (2016T90780), the Fundamental Research Funds for the Central Universities (2015NM027), the Open Foundation of the State Key Laboratory of CAD&CG of Zhejiang University (A1508), and the Science & Technology Research Program of Guangdong (2016A030310409). Great thanks are also given to the anonymous reviewers for their comments and suggestions, which helped us to improve the manuscript.
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