Statistical shape modeling in virtual assembly using PCA-technique

The use of virtual assembly tools is one way to understand and improve the geometric product tolerance setting and the conditions for successful manufacturing. Recent developments enable consideration to be given to the deformability of parts (single components or subassemblies) when joined. In order to produce reliable results, the geometric deviations of the mating surfaces must be correctly assumed. In this paper, statistical shape models built on the Principal Component Analysis-technique (PCA) are proposed to be used to describe the part variation. A generalized model is presented and the underlying intentions and implications are discussed. It is demonstrated how the PCA-technique can be applied on bigger structures. The method is exemplified using the software RD&T. In the presented case, a non-rigid sheet metal assembly is modeled and distorted to create a set of sample shapes from which a statistical model is built. In the result, the statistic representation bears a good resemblance to the distorted nominal model when the two are compared.