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Proceedings of CAD'15, 2015, 91-94
Retrieval of Solid Models based on Assembly Similarity

Rahul Sharan Renu, Gregory Mocko, Clemson University

Abstract. The objective of this research is to extend existing solid model retrieval algorithms to aid in assembly process planning. Specifically, a new algorithm is developed using geometric information from components and assemblies to enable the reuse of assembly work instructions. The hypothesis tested in this research is that similar geometric models of assemblies will have similar assembly work instructions. This research enables manufacturing engineers to reuse existing assembly work instructions (based on solid model similarity) in a systematic manner, thus reducing the effort expended in the assembly planning process. A two-level solid model similarity algorithm is developed and validated. At the first level, the geometric similarity of between two assemblies is computed by determining the similarity of the individual components in each assembly. At the second level, the similarity is computed between the two assembly models. This two level approach is justified because the individual components within an assembly may be configured differently. It is hypothesized that the two-level approach will increase the accuracy of retrieved assemblies as compared to the existing algorithms for computing similarity between solid models. The algorithm developed in this research combines existing shape histogram similarity and surface area similarity with tessellation density differences.

Keywords. Solid model similarity, Knowledge reuse, Assembly work instructions, Shape histogram, Tessellation density

DOI: 10.14733/cadconfP.2015.91-94