The mechanically-induced transformation behaviour of the metastable austenite phase in a high-strength industrial TRIP-assisted Dual Phase steel was monitored in situ using high-energy synchrotron diffraction under uniaxial loading. This allowed direct quantification of the impact of the transformation of the metastable austenite phase (16 vol %), embedded in a ferrite-bainite-martensite matrix, on the work hardening behaviour of this steel. Our results show that the mechanically induced transformation of austenite does not begin until the onset of matrix yielding. We provide experimental evidence which demonstrates for the first time that the austenite transformation increases the work-hardening contribution, σw thereby supporting a driving force approach to transformation induced plasticity. The transformation work required leads to an increase in the macroscopic work-hardening rate after matrix yielding and continues to offset the decrease in the work-hardening rate in the ferrite and martensite phases up to the UTS. Further we show conclusively that martensite yielding does not occur until the completion of the mechanically induced transformation of austenite. Plastic deformation of martensite is immediately followed by local plastic instability leading to necking and ultimate failure of this material

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Robust processes and robust engineering are enjoying increasing interest throughout industry. Robust engineering is taking into account variations that can occur during manufacturing processes when we analyse or optimise them. Corus is interested in robust engineering, being a supplier of steel not just for its own processes but also for supporting customers. Robust engineering, if properly applied to e.g. the stamping process, ensures that the customer's forming process is stable and insensitive to material and process variations, thus reducing scrap rates. To analyse a stamping process for robustness input in terms of variation in process and material properties is needed. As a material supplier we focus on the variation in material properties. This paper deals with the effect of the material models used in simulation on the prediction of process variations as well as scrap rate. The effect of models on the variation itself is small, however, the effect on the average (and hence on e.g. scrap rate) is significant. Some examples of the capabilities of commercial software are also added.

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