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Robustness, optimization and Finite Element (FE) simulations are of major importance for achieving better products and cost reductions in the metal forming industry. In this paper, a metamodel-based robust optimization strategy is proposed for metal forming processes. The applicability of the strategy is demonstrated by application to an analytical test function and an industrial V-bending process. The results of both applications underline the importance of including uncertainty and robustness explicitly in the optimization procedure.

Sandvik NanoflexTM combines good corrosion resistance with high strength. The steel has good deformability in austenitic conditions. This material belongs to the group of metastable austenites, so during deformation a straininduced transformation into martensite takes place. After deformation, the transformation continues as a result of internal residual stresses. Depending on the heat treatment, this stress-assisted transformation is more or less autocatalytic. Both transformations are stress-state, temperature and crystal orientation dependent. This article presents a constitutive model for this steel, based on the macroscopic material behaviour measured by inductive measurements. Both the stress-assisted and the strain-induced transformation to martensite are incorporated in this model. Path-dependent work hardening is also taken into account, together with the inheritance of the dislocations from one phase to the other. The model is implemented in an internal Philips code called CRYSTAL for doing simulations. A multi-stage metal forming process is simulated. The process consists of different forming steps with intervals between them to simulate the waiting time between the different metal forming steps. During the engineering process of a high precision metal formed product often questions arise about the relation between the scatter on the initial parameters, like standard deviation on the strip thickness, yield stress etc, and the product accuracy. This becomes even more complex if the material is: • instable, • the transformation rate depends on the stress state, which is related to friction, • the transformation rate depends on the temperature, which is related to deformation heat and the heat distribution during the entire process. A way to get more understanding in these phenomena in relation to the process is doing a process window study, using DACE (Design and Analysis of Computer Experiments). In this article an example is given how to make a DACE study on a a three stage metal forming process, using a distributed computing technique. The method is shown, together with some results. The problem is focused on the influence of the transformation rate, transformation plasticity and dilatation strain on the product accuracy.