Assembly Information Modeling via the Cognition of Interaction Structures for Digital-Twin Based Assembly

To model assembly information between parts in terms of CAD solid models efficiently and accurately for digital-twin based assembly, an approach based on the cognition of interaction structures between part models is proposed. The approach combines the previously developed concept of Interaction Feature Pair (IFP) and BDI (Belief-Desire-Intention) cognitive behavior model. In this approach, part models are firstly associated with IFPs and treated as BDI agents. Then, algorithms to build part models' believes, desires and intentions are designed, to make them mate with each other autonomously based on IFP matching. On this basis, assembly information including connection relationships, support relationships and interference relationships, between part models is extracted by analyzing the IFP matching results. Finally, the effectiveness of the proposed method is demonstrated by two examples. This method has positive significance for studying the cognitive behavior of parts and extracting assembly information.