Function-Based Synthesis of Combined Mechanisms by Clustering Fine-Grained Function Units in the Form Layer

Conceived functional hierarchies closely related to building blocks and the lack of sufficient and explicit knowledge to describe the relationship between a combining mechanism and its constituent mechanisms are two barriers for AI-based functional synthesis tools to explore novel combined mechanisms. This paper handles this difficulty by clustering a group of fine-grained function units (SKBs) into a well-organized and complete kinematic behavior that can match a subfunction and be implemented by a constituent mechanism based on the consistency and compatibility conditions among SKBs. The likelihood of clustering a group of SKBs into a subset of SKBs depends on the indicators of correlation between SKBs, between the subset of SKBs and its corresponding realized functional behavior, and the corresponding embodied mechanism. According to the largest correlation index, a group of SKBs in the form layer can be clustered into a subset of SKBs that perform a well-organized and complete kinematic behavior, which can be achieved by a combined mechanism with an optimal structure related to the subfunction. The advantage of the proposed approach is that the synthesized combined mechanisms can realize the overall function of the design problem organically and synergistically. Moreover, since multiple functional behaviors of each constituent mechanism participate in function-form matching, it may be possible to explore novel combinations of mechanisms with fewer and simpler constituent mechanisms.