In this paper

the deep groove plunge milling process of nickel-based super-alloys was researched. Taking material removal rate and residual height as the optimization goals

a process parameter optimization model under the constraints of cutting force and stability was proposed. The weight of each target was difficult to quantify and adjust  when the objective function was established by the weighting method. Aiming at the problem

the ratio weighting method was used to establish the objective function to ensure the balance of the optimization direction. The genetic algorithm was used to solve the optimization model example

and the performance indicators of the optimization results and empirical results were compared. The results show that when the constraints are met

the optimized process parameters can not only significantly increase the material  removal  rate

 but also control the  residual height

 so as to achieve high-efficiency and  high-quality processing.