Effect of cutting parameters on tool wear under minimum quantity cooling lubrication (MQCL) conditions

Abstract

This paper presents the effect of cutting parameters on tool wear under minimum quantity cooling lubrication (MQCL) conditions. Turning AISI 304 stainless steel was carried out using VAMF-1 environmentally friendly cutting fluid under MQCL conditions, for which 27 groups of all-factor experiments were utilized. The tool wear results showed that the most effective parameter was the cutting speed (relative contribution of 46.725%), followed by the feed rate (relative contribution of 28.120%). According to the tool vibration results, the cutting speed was the most important parameter, followed by the feed rate and the cutting depth. During low-speed cutting, a larger feed rate and cutting depth could be selected, for which adhesive wear is the prevailing mechanism. As the cutting speed increased, the built-up edge (BUE) near the cutting edge disappeared and the adhesives fell off; diffusion wear was the main mechanism in this case. In addition, a prediction model was constructed with the objective of surface finish and tool wear, and the results were optimized by an improved fruit fly optimization algorithm (FOA). The verification experiment results showed that the prediction errors of VB and Ra were 2.15% and 6.48%, respectively. Moreover, MQCL achieved better surface quality and lower tool wear than minimum quantity lubrication (MQL) and dry cutting under the optimized parameters.