Abstract: To enhance the machining quality and efficiency of 440C stainless steel parts used for the aviation valves, a study on the optimization of grinding process parameters was conducted based on response surface methodology (RSM) and multi-objective grey wolf optimizer (MOGWO). Regression models for surface roughness and cylindricity were established separately using RSM. The interactive effects of grinding parameters on the surface roughness and cylindricity of the specimens were clarified through analysis of variance and response surface plots. By considering both machining quality and efficiency, the MOGWO algorithm was employed to obtain a Pareto solution set for multi-objective optimization of grinding process parameters. The decision solution was derived by integrating the analytic hierarchy process (AHP) and the technique for order preference by similarity to ideal solution (TOPSIS). The results demonstrate that, while ensuring machine quality, the material removal rate was increased by 20%, indicating significant engineering application value.