Multi-response optimization of the actively driven rotary turning for energy efficiency, carbon emissions, and machining quality

Boosting energy efficiency and machining quality are prominent solutions to achieve sustainable production for turning operations. In this work, a machining condition-based optimization has been performed to decrease the total specific energy (SEC), carbon emission (CE), and average roughness (AR) of the actively driven rotary turning (ADRT) process. The processing factors are the tool rotational speed (T-v), depth of cut (a), feed rate (f(r)), and workpiece speed (W-v). The turning experiments of the mold material labeled SKD11 have been conducted on a CNC lathe. The regression method is employed to develop comprehensive models of the total specific energy, carbon emissions, and average roughness. The entropy approach is then applied to drive out the weight value of each ADRT response. Finally, the non-dominated sorting particle swarm optimization (NSPSO) is utilized to determine the optimal parameters. The findings indicated that the optimal values of the T-v, a, f(r), and W-v are 77 m/min, 0.32 mm, 0.25 mm/rev., and 128 m/min, respectively. The SEC, AR, and CE are decreased by 18.07%, 10.46%, and 5.02%, respectively, as compared to the initial approach. Moreover, the developed active rotary turning operation can be considered as an effective technical solution to boost the machining efficiency of hardened steels.

Automated summary

The study focuses on optimizing energy efficiency and machining quality in the actively driven rotary turning (ADRT) process, reducing total specific energy, carbon emissions, and average roughness. By conducting experiments and utilizing optimization techniques, optimal parameters were determined, leading to a significant decrease in energy consumption, emissions, and roughness, showcasing an effective technical solution to boost machining efficiency of hardened steels.