Taps are widely used in the thread machining system. However, excessive loads during the tapping process can increase tap wear, which can affect tap life. Therefore, effective methods need to be proposed to solve the problems of excessive load and severe wear during tap tapping. This articleproposes a geometric parameters (e.g. rake angle (K_y), cone angle (K_r), helix angle (K_h), etc.) optimization method based on response surface methodology (RSM) and nondominated sorting dung beetle optimization algorithm for a tap, exemplified through the tapping process of 304 stainless steel. This method is based on axial force (F_a) and torque (T). Firstly, the finite element model for the tapping process of 304 stainless steel is established, and the orthogonal simulation is carried out. Secondly, predictive models of F_a and T are established according to the RSM. The interaction effects of geometric parameters on F_a and T are revealed. After that, the nondominated sorting dung beetle optimization algorithm is implemented for the optimization of K_y, K_r, and K_h. The TOPSIS evaluation model is introduced to evaluate the Pareto optimal solution. Finally, some verification experiments are finished. The optimized tap shows a reduction in average axial force by 44.69 N and a decrease in average torque by 2.67 N·m. Under the same conditions, the flank wear width is reduced by 15.71%. The optimization method of tap geometry parameters in this paper is proposed based on finite element simulation and intelligent optimization algorithm. This method can provide technical guidance for the optimization of tool geometric parameters.

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Geometric parameters optimization of tap via response surface methodology and nondominated sorting dung beetle optimization algorithm

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Geometric parameters optimization of tap via response surface methodology and nondominated sorting dung beetle optimization algorithm