Optimization of milling parameters of thin-walled parts based on Kriging-MIGA algorithm

Aiming at the machining deformation problem of an aluminum alloy thin-walled shell part, with the milling force as the optimization goal, through the Isight platform, a milling parameter optimization method based on the Kriging-MIGA algorithm is proposed. The optimal Latin hypercube experimental design method was used to establish the parameter sample points, and the Kriging approximate model between the milling parameters and the milling force was built using the sample points. The MIGA algorithm was used to globally optimize the approximate model, and a set of milling that could minimize the milling force was obtained. Combine the parameters and get the predicted value. The research results show that the optimization of milling parameters based on the Kriging-MIGA algorithm reduces the milling force by 39.37% and effectively reduces the deformation of the aluminum alloy thin-walled shell. The research method in this paper is of great significance to the selection of milling parameters of thin-walled parts.