Predicting Dimensional Deviations of Structural Vehicle Body Parts Deep Drawn from Aluminum Blanks

摘要

Because of the extensive manufacturing chain in the present automotive mass production environment, deviations can have a large impact. Rerouting knowledge about deviation behavior back from production into development is crucial for the quality of the product. This study aims to make deep drawing deviations of aluminum body sheets more traceable. Geometrical measurements of a sample part are compared to the part's topology. Similarities between local stiffnesses and deviations can be detected and quantified by a higher-order polynomial, making it easier to predict deviations. Moreover, the standard deviations and mean values are analyzed regarding the topology.