Intelligent assembly modeling of complex product based on cognition of interaction structures

Abstract

Interactions of a part with other parts in an assembly constitute the behavior of the part. However, currently parts interact with each other lifelessly in assembly environment due to their incapability of cognizing interaction structures between them, making the assembly modeling of complex products suffer from considerable manual interventions. An intelligent assembly modeling method is proposed for complex products in this paper, by endowing parts with the ability of cognizing interaction structures between them. In this method, the concept of interaction feature pair (IFP) and the corresponding automatic construction algorithms are developed to explicitly describe interaction intent (i.e., how a part will mate with other parts) in designer’s mind, providing carriers for part cognition behaviors and dynamical interaction intent in the assembly modeling process. On this basis, an object-oriented product information model considering IFP is established to facilitate the complete capture of interaction intent at part modeling stage and the consistent transmission of it to assembly modeling stage, endowing parts with the cognition ability of foreseeing how to mate with other parts before and after loading into assembly modeling environment. Then, IFP matching algorithms are designed to support the part cognition behaviors of actively cognizing interaction structures, perceiving potential mating parts and mating with other parts with high efficiency. Assembly modeling case studies of a reducer and a Mecanum wheel with few manual interventions indicate the feasibility of the proposed approach.