Multi-Objective Optimization of Process Parameters in Longitudinal-Torsional Ultrasonic Vibration Face Grinding CFRP

Abstract

Due to its superior characteristics, carbon fiber reinforced plastics (CFRP) have been widely used in aerospace and other fields. However, their effective and economical processing remains a challenge. The purpose of this paper was to experimentally investigate the influence of several machining parameters, namely spindle speed, cutting depth, feed rate, and grit size on different machining performances, i.e., grinding force, and surface roughness through longitudinal-torsional (L&T) ultrasonic vibration grinding CFRP. The response surface methodology with a Box—Behnken design was used to create the experiments. The fitting mathematical models of grinding force and surface roughness were established separately to explore the interaction between the machining parameters and the impact on machining results. With the purpose of improving the surface quality and reducing the grinding force, the NSGA-II was used for multi-objective optimization to obtain the Pareto optimal solution. Compared with the initial experimental parameters, the optimized results can significantly improve the surface roughness and reduce the cutting force.