Optimization of Milling Process Parameters for Fe45 Laser-Clad Molded Parts Based on the Nondominated Sorting Genetic Algorithm II

The milling process parameters of laser-clad molded parts have an essential influence on improving the surface quality of the coating. Generally speaking, optimizing a single property often leads to a reduction in another property. In this paper, we systematically investigated a milling process parameter optimization method for Fe45 laser-clad molded parts, and designed L9 (33) sets of orthogonal experiments by taking the spindle speed, feed rate, and cutting depth as input variables, and taking the milling force and material removal rate as optimization indices. The significance ranking of the milling process was analyzed by using the extreme difference method. Then, the multi-objective optimization of the milling process was realized by using the NSGA-II algorithm with the empirical index model as the objective function. The optimum milling parameters obtained were N = 2000 r/min, V = 120.0266 mm/min, and P = 0.45 mm. Finally, the reliability of the optimization results of the algorithm was proved by comparing and verifying the optimal results obtained from the algorithm with the optimal process obtained from the extreme difference analysis. The results provide a theoretical basis for the selection of milling parameters and parameter optimization of laser fusion-coated Fe45 alloys.