The punching process of AHSS induces edge cracks in successive process, limiting the application of AHSS for vehicle bodies. Controlling and predicting edge quality is substantially difficult due to the large variation in edge quality, die wear induced by high strength, and the complex effect of phase distribution. To overcome this challenge, a quality prediction model that considers the variation of the entire edge should be developed. In this study, the image of the entire edge was analyzed to provide a comprehensive evaluation of its quality. Statistical features were extracted from the edge images to represent the edge quality of DP780, DP980, and MART1500 steels. Combined with punching monitoring signals, a prediction model for hole expansion ratio was developed under punch conditions of varying clearance, punch angle, and punch edge radius. It was found that the features of grayscale variation are affected by the punching conditions and are related to the double burnish and uneven burr, which degrades the edge quality. Prediction of HER was possible based on only edge image and monitoring signals, with the same performance as the prediction based solely on punching parameters and material properties. The prediction performance improved when using all the features.

This study analyzes a three-stage roll flattening process to improve the flatness of 1.5 GPa grade AHSS sheets. Unlike conventional leveler rolls, which mainly relieve residual stress through longitudinal tension-compression, the second roll has a sloped pattern to induce transverse deformation and redistribute local residual stresses. A twisted sheet was processed under different roll gap settings (1.3 mm, 1.1 mm, 0.9 mm, and 0.7 mm), and experimental measurements were compared with Abaqus Explicit simulations. At a 1.1 mm gap, the RMSE between experiment and simulation is 0.22 mm, showing the highest agreement. Both twist and crossbow defects are reduced by over 80%, achieving optimal flattening. At 1.3 mm, the simulation overestimates the second roll’s effect, causing excessive localized deformation. Reducing the gap to 0.9 mm or 0.7 mm increases discrepancies due to roll fixation differences. Experiments allow more central bending, amplifying crossbow, while simulations assume rigid rolls, underestimating curvature. Adjusting the second roll’s geometry to enhance transverse tension-compression and setting the gap to 1.1 mm effectively reduces defects. This method improves flatness while minimizing the number of rolls needed in high-strength steel sheet production.

Predicting bending fractures in advanced high-strength steel (AHSS) is challenging due to complex microstructural behaviors and strain rate dependencies, particularly in industrial forming processes. Current models and standards primarily focus on quasi-static tension or slow bending speeds, leaving a gap in understanding the accelerated failure of AHSS without necking. In this study, direct bending experiments were conducted on dual-phase, complex-phase, and martensitic AHSS grades under varying bending speeds and radii. Since the bending crack is irrelevant to the load drop, surface crack evolution was measured using three-dimensional surface profile analysis. The results showed that accelerated bending significantly delayed crack initiation across all tested materials, with small-radius bending showing reduced strain localization due to strain rate hardening. Larger-radius bending benefited primarily from increased fracture strain.