Surface integrity investigation and multi-objective optimization in high-speed cutting of AISI 304 stainless steel for dry cutting and MQCL conditions

To realize green production in the manufacturing industry, it is important to reduce or even eliminate the discharge of cutting fluid. In this study, the impact tendency of the cutting parameters on the surface roughness of 304 steel was analyzed by establishing variance analysis models. The surface quality profile parameters and the main cutting force under minimum quantity cooling lubrication (MQCL) and dry cutting conditions were analyzed and compared. The characterization of the morphology of the machined surface was evaluated, and the wear mechanisms of the two machining methods were analyzed. A hybrid machining strategy was developed in which dry cutting is used at the beginning of cutting and dry cutting is replaced with MQCL before the quality of the machined surface deteriorates sharply. This strategy obtains the optimal parameter combination through a genetic algorithm. The most important factor affecting the surface roughness was the feed rate, whereas the change in cutting depth had no obvious effect on the surface roughness. In addition, the parameters of low cutting speed and feed rate were advantageous under dry cutting conditions. However, with increases in the feed rate and cutting speed, the peak and valley of the surface profile gradually increased, and the MQCL conditions were more conducive to obtaining a smoother surface. Furthermore, the MQCL and higher cutting speed could reduce the main cutting force. The surface roughness under hybrid cutting was 5.19% and 18.76% lower than that under MQCL and dry cutting, respectively.