Abstract
In this study, the cutting parameters for machining deep bottle holes (deep holes with complex profiles and length-to-diameter ratio greater than 10) were optimized based on cutting simulation, a regression analysis genetic algorithm, and experimental validation. The influence of cutting parameters on cutting force and cutting temperature was analyzed using the response surface method (RSM), and the regression prediction model of cutting parameters with cutting force and most cutting temperature was established. Based on this model, multi-objective optimization of cutting force F(x) and material removal rate Q was carried out based on a genetic algorithm, and a set of optimal cutting parameters (v = 139.41 m/min, a(p) = 1.12 mm, f = 0.27 mm/rev) with low cutting force and high material removal rate were obtained. Finally, based on the optimal cutting parameters, the machining of TC4 deep bottle holes with a length-to-diameter (L/D) ratio of 36.36 and a roughness of Ra 3.2 µm was accomplished through a deep hole boring experiment, which verified the feasibility of the selected cutting parameters and provided a certain reference for the machining of this type of parts.