Multi-objective optimization of cutting parameters for ultrasonic vibration hard drilling of 42CrMo steel

Minimizing the adverse environmental effects of manufacturing while reducing costs and maintaining machining quality is essential for achieving sustainable development. The optimization of drilling parameters is directly related to several crucial indicators of machining technology. This work aims to explore the influence of drilling parameters and ultrasonic parameters on carbon emissions, machining costs and machining quality during ultrasound-assisted hard drilling of 42CrMo steel. The goals of low carbonization, low cost and high quality in the hard drilling processing of this material could be achieved. Initially, mathematical models for the three indices are established. Subsequently, the multi-objective particle swarm optimization algorithm (MOPSO) and the non-dominated sorting genetic algorithm with elite strategy (NSGA-II) are utilized to solve these models, respectively. The results show that after MOPSO optimization, carbon emissions, machining costs and surface roughness have decreased by 9.75 %, 4.54 % and 20.61 % respectively compared with the optimization results of NSGA-II. The optimization performance of MOPSO is superior to that of NSGA-II. Furthermore, spindle speed and feed rate are the key parameters influencing carbon emissions and machining costs, respectively, while ultrasonic amplitude significantly impacts surface roughness. This research provides essential theoretical support and practical guidance for achieving the integrated optimization of environmental, economic, and machining quality in hard drilling process. It significantly promotes the application of green manufacturing in precision machining and facilitates the realization of sustainable manufacturing goals.