Stamped part classification and automatic dieface design

Abstract

In the context of weight reduction for new car design, it is essential to downsize, or rather optimize, the Body In White (BIW) structure. A very effective approach is to take into account the influence of Manufacturing process in the performance analysis such as crash or fatigue. Further, integrating the interaction between Stamping and Crash performance should also improve the predictability of the CAE approach and lead to more efficient design. One-step simulation of sheet metal forming is a very promising technology for this application, as it can be used on the same mesh as crash analysis and can work with a simplified dieface. However, a Dieface, although simplified, must be generated for nearly all parts of the vehicle model. Hence, the implementation of product-process coupling on an industrial scale requires the development of methodologies for automatic dieface design imbedding sheet metal forming expertise. Dieface generation depends on the geometrical features of the part, but we understand the latter only if we have a framework in terms of dieface features. The authors show that such a development requires an innovative approach to stamped part classification, based both on the geometrical features of the part and on the possible strategies in dieface development. Beside its novelty, this classification has the advantage of using a decision tree based only on a vector of quantitative features, thus making it possible to implement it in automatic decision support software. An application based on a real world BiW is presented.