Abstract
The majority of parts in modern car bodies is manufactured from sheet metal. Rarely these parts are fully stressed due to design space restrictions and complex requirements. The usage of tailor rolled blanks (TRB) enables the reduction of sheet thickness in areas less loaded and thus reduces part weight. Technically most sheet metal parts are potentially suited for the application of TRB. Economic circumstances like the additional flexible rolling process and technology-specific nesting constraints limit the application to a subset of parts. The search for the best candidate parts taking mass and cost into account is currently challenging. This article presents an optimization strategy for the selection of the parts in a vehicle structure that are best suited for the application of TRB. As a first step, a priori preferencing is performed to select parts based on engineering rules. Using a reduced number of candidate parts, high quality metamodels are trained to perform multiobjective optimizations of all possible combinations of remaining parts, revealing the most efficient part selection under consideration of mass and cost.
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