Statistical analysis of forming processes as a first step in a process-chain analysis: Novel PRO-CHAIN components

This paper presents a new approach for statistical analysis of process chains, including a parameter sensitivity analysis of each process step as a basis for dimension reduction, and an efficient interpolatory metamodel in order to predict new designs. A Monte Carlo alike evaluation of this metamodel results in the requested statistical information, e.g. quantiles of the output functionals. Numerical results are presented for the forming process of a ZStE340 metal blank of a B-pillar. Additionally, a brief overview of results of the process chain forming to crash is given.