Multi-Response Optimization Of Machining Parameters In CNC Turning Of AISI 316L Stainless Steel Using MQL Nano fluids

In this research work, optimization of machining parameters in plain turning operation to minimize surface roughness and cutting temperature by applying Taguchi based Desirability function analysis and ANOVA method under Nano cutting fluid environment is performed. Experiments have been performed by plain turning of AISI 316L stainless steel on CNC lathe under MQL setup with Multi-walled carbon Nanotube (MWCNT) inclusions using carbide inserts. Carbon Nano tubes are mixed in a specific ratio (0.20% by wt.) with the cutting fluid. The impact of input parameters on the response variables such as surface roughness and cutting temperature are analysed by using desirability function based approach. Experimental results reveal that feed rate is said to have more effect on the response variables followed by depth of cut, type of cutting fluid and spindle speed.