Tool Wear Prediction in the Forming of Automotive DP980 Steel Sheet Using Statistical Sensitivity Analysis and Accelerated U-Bending Based Wear Test

Abstract

The forming process of ultra-high-strength steel (UHSS) may cause premature damage to the tool surface due to the high forming pressure. The damage to and wear of the tool surface increase maintenance costs and deteriorate the surface quality of the sheet products. Hence, a reliable prediction model for tool wear can help in the efficient management of the quality and productivity of formed sheet products of UHSS. In this study, a methodology is proposed for predicting the wear behavior of stamping tools that are used in the forming process of DP980 steel sheet. Pin-on-disk tests were conducted based on the Taguchi method to develop the tool wear prediction model. Using statistical analysis based on the signal-to-noise (S/N) ratio and ANOVA result, the contact pressure and the sliding distance were selected as the major contact parameters for tool wear. The Archard wear model has a limitation in predicting the nonlinear behavior of tool wear. Therefore, the power-law nonlinear regression model as a function of the contact pressure and the sliding distance was constructed. To verify the reliability of the constructed tool wear prediction model, the U-draw bending tests were designed. The modified U-draw bending test, which accelerates tool wear, is newly designed to evaluate the tool wear for different contact pressures and sliding distances. The modified die generated a contact pressure four times higher than that of the conventional die from the finite element (FE) simulation results. The tool wear prediction model was validated by comparing the predicted results with the experimental results of DP980 sheets formed using the physical vapor deposition (PVD) CrN-coated STD11 tool steel.