A heuristic approach to detect CAD assembly clusters

Mechanical assemblies are very complex structures, made of many parts of various shapes and sizes with different usages. Consequently, it is challenging to manage them during all the manufacturing processes, from the design to the assembly and the recycling. Aiming to simplify the assembly structure and reduce the number of parts to deal with simultaneously, in literature many works exist on subassemblies identification starting from the CAD assembly model. However, the methods provided loose sight of many details associated with the parts, as well as the fact that the treated model represents a real mechanical assembly which respects precise engineering rules. At this regard, this work introduces a novel methodology to detect meaningful clusters in CAD assembly models. The logic applied relies on engineering knowledge, both of mechanical assemblies' components and of assembling techniques, and on the leveraging of the semantics of components. In particular, referring to general design rules, we have identified some heuristics to exploit to partition the assembly into different types of clusters, such as the symmetry along an axis and the presence of fasteners or welds. It results that the assembly's parts are meaningfully grouped, considering, at the same time, their shape, functionality, and type of contact.