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Springback compensation studies on a few selected auto panels from the hot selling Chrysler 300C are presented with details. LS-DYNA® is used to predict the springback behavior and to perform the iterative compensation optimization. Details of simulation parameters using LS-DYNA® to improve the prediction accuracy are discussed. An iterative compensation algorithm is also discussed with details. Four compensation examples with simulation predictions and actual panel measurement results are included to demonstrate the effectiveness of LS-DYNA® predictions. An aluminum hood inner and a high strength steel roof bow are compensated, constructed and machined based on simulation predictions. The measurements on actual tryout panels are then compared with simulation predictions and good correlations were achieved. Iterative compensation studies are also done on the aluminum hood inner and the aluminum deck lid inner to demonstrate the effectiveness of LS-DYNA® compensation algorithm.

The springback behavior might be different due to different gap clearances between die and punch. A study using FEA simulation is done to investigate the die gap effect. A 3D brick element and an explicit-implicit method are employed to investigate a few simple problems. A draw form, a crash form with an upper pad and a flange form are investigated separately. Numisheet’93 2D draw bending springback problem is also investigated using an explicit dynamic code. Comparisons between springback simulation results on several different die gaps are illustrated. The Kirchhoff assumption of C° shell element and the Mindlin/Love assumption of thin shell element are also examined on different cases. A case study then is performed on a rail type panel. Conclusions and recommendations for future studies are summarized.

Springback study on a Dodge Ram fender outer panel is detailed in this paper. A simple measurement fixture is designed for the panel, wherein non-contact laser scan technology is applied The measurement data are compared with the original CAD design surface and deviation contour maps are obtained. Consistency of measurement is studied at different sections among three samples. Details of FEA simulations are outlined. The comparison between measurement and simulation prediction is summarized. A method to describe the consistency of measurement and the accuracy of simulation prediction is proposed. The targets for measurement consistency and simulation accuracy are verified. A sensitivity analysis is also performed to investigate various simulation input parameters.