Optimization of Rough Self-Propelled Rotary Turning Parameters in terms of Total Energy Consumption and Surface Roughness

Abstract

The self-propelled rotary tool turning (SPRT) process is an economic and effective solution for machining difficult-to-cut materials. This work optimized SPRT parameters, including the inclination angle (A), depth of cut (D), feed rate (f), and turning speed (V) to decrease the total energy consumption (TE) and surface roughness (SR). The turning experiments of the hardened AISI 4150 steel were executed to obtain the experimental data, while the regression method was applied to develop the TE and SR correlations. The entropy method and quantum-behaved particle swarm optimization (QPSO) were utilized to select the weights and optimal factors. The results indicated that the optimal A, D, f, and V were 34 deg., 0.40 mm, 0.47 mm/rev., and 177 m/min, respectively, while the TE and SR were saved by 9.7% and 35.4%, respectively. The f and V were found to be the most effective parameters, followed by the D and A. The outcomes provide valuable data to determine optimal SPRT factors for minimizing energy consumption and maximizing machining quality.The optimizing technique could be applied to solve other issues for different SPRT operations.

Keywords

• entropy
• process parameters
• QPSO
• self-propelled rotary tool turning
• surface roughness
• total energy consumption