Multi response optimization of nozzle process parameters in MQL assisted face milling of AISI 52,100 alloy steel using TGRA

Abstract

Abstract The demand for near dry machining increases due to the adverse effect of cutting fluid on health and the environment. MQL technique offers itself as a suitable alternative for cooling and lubrication at the cutting zone during machining. In MQL mixture of a very low quantity of lubricant and compressed air is sprayed at the cutting area. Economic factor also makes it desirable as it reduces the cutting fluid cost. In this paper, the effect of MQL parameters on surface roughness and temperature during face milling of AISI 52,100 alloy steel is studied. The MQL nozzle parameters, the nozzle elevation angle, and the spray distance were selected as a process variable. A full factorial design was used to conduct the experimentations on a vertical machining center; the analysis was done by using the Analysis of variance (ANOVA) approach. A higher value of grey relational grade gives the best combination of MQL parameters for both output responses (surface roughness and temperature). The result shows that the nozzle elevation angle at 450 and a spray distance of 40 mm was the optimum process variable for both the excellent surface finish of the work piece and low temperature at the cutting zone.