An efficient method for thickness prediction in multi-pass incremental sheet forming

Abstract

Incremental sheet forming (ISF) is a highly versatile and flexible process for rapid manufacturing of complex sheet metal parts. In the ISF process, efficient and accurate prediction of part thickness variation is still a challenging task, which is especially true for the multi-pass ISF process. The Sine law equation and the finite element method (FEM) are the two commonly used conventional prediction methods. However, these approaches are either with limited accuracy or very time consuming. For the multi-pass ISF process, the thickness prediction is even more challenging since two or more forming steps are involved. Focusing on the thickness prediction of multi-stage ISF process, this work proposes a thickness prediction model based on the geometrical calculation of intermediate shapes of the formed part and backward tracing of nodal points of the forming tool. By developing this method, the thickness distribution can be calculated through the predicted nodal displacement in the ISF process. To verify the proposed model, four different geometrical shapes, i.e., conic, parabolic conic, non-axisymmetric, and hemispherical parts, are physically formed by using a NC ISF machine. The geometric shapes and the detailed thickness distributions of the formed parts are carefully measured and compared with the prediction model developed. Good agreements between the analytical predictions, and the experimental results are obtained. This indicates the effectiveness and robustness of the developed thickness prediction approach.