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Recently, in order to improve crashworthiness and achieve weight reduction of car body, a hot stamping process has been applied to the production of the part with tailored properties using tailored tool thermomechanical treatment. In the tailored tool thermomechanical treatment process, process parameters influence the mechanical properties of final product such as strength and hardness. Therefore, the prediction of hardness for final product is very important to manufacture hot-stamped part considering various process parameters. The purpose of this study is to propose a process window, which can predict hardness for various process parameters in tailored tool thermomechanical treatment. To determine the process window, finite element (FE) simulation coupled with quench factor analysis (QFA) has been performed for combinations of various process parameters. Subsequently, the process window was constructed through the training of artificial neural network (ANN) and experiment of tailored tool thermomechanical treatment for hat-shaped part was performed to verify effectiveness of hardness prediction. Then, the process parameters were determined from process window for hot stamping of the hat-shaped part with the required distribution of hardness. Hardness predicted by process window was in good agreement with measured one within 3.1% error in additional experiment. Therefore, the suggested process window can be used efficiently for hardness prediction and determination of process parameters in tailored tool thermomechanical treatment of hot-stamping parts.

Construction of Process Window to Predict Hardness in Tailored Tool Thermomechanical Treatment and its Application