Investigation on surface roughness in elliptical ultrasonic vibration-assisted ultra-precision cutting process of SiCp/Al composites based on particle swarm optimization algorithm

SiCp/Al, as a typical metal matrix composite material, has important applications in the field of aerospace optical devices. For the surface defect control difficulties caused by the crushing of SiC particles in its ultra-precision cutting, this paper proposes a surface roughness prediction model based on elliptical ultrasonic vibration-assisted machining. At the same time, according to the response surface graph obtained from Design-Expert software analysis, the influence of three cutting process parameters on surface roughness and the interaction between cutting parameters were analyzed. Finally, the improved MOPSO algorithm is used to optimize the machining parameters, and the experimental validation is compared to get the prediction error of the model is less than 10%, which indicates that the prediction model is effective and reasonable, and it can provide a theoretical basis for the efficient and precise machining of hard and brittle composite materials.