A 6-sigma robust optimization method for stamping forming of automobile covering parts based on residual error and radial basis interpolation

Reducing the disturbance of parameter fluctuations to the system is very important to the robustness of stamping product quality. In this paper, a 6-sigma robust optimization design method based on residual error and radial basis interpolation is proposed to weaken the negative influence of parameter fluctuations. Not only the key controllable parameters but also the key noise parameters are considered by grey relational analysis (GRA) to screen the parameters that have an important influence on the stamping quality. In order to reflect the relationship between key parameters and forming quality more precisely, the polynomial response surface model is improved based on residual error and radial basis function (RBF), and solved by the multi-population co-evolutionary immune algorithm (MPCEIA). Moreover, the solution of deterministic optimization is designed with 6-sigma robust optimization to improve the robustness of the system to the parameter fluctuations. Finally, the method is applied to the design of a complex automobile cover part, proving its effectiveness and reliability.