For the optimization of milling parameters in CNC machine tools,conventional reliability approximation models are often used,but this method is susceptible to the influence of material failure strain coefficient,resulting in lower processing efficiency after optimization.Therefore,an optimization method for milling parameters of CNC machine tools based on an improved genetic algorithm was proposed.Based on the constitutive model of the workpiece,the cutting edge was sampled and extracted to determine the minimum milling force fluctuation position.The material failure criterion was introduced to calculate the material failure strain coefficient.Based on this,a milling parameter optimization model was established with the goal of minimizing processing time and processing cost.An improved genetic algorithm was used to solve the model,and the optimal milling parameters were output through iterative fitness values.Finally,the optimization performance of the proposed method was tested through comparative experiments.The test results show that applying the proposed method to optimize the milling parameters of CNC machine tools can effectively shorten cutting time and improve machining efficiency.