Experimental investigation and optimization of cutting parameters with multi response characteristics in MQL turning of AISI 4340 using nano fluid

To increase the productivity in machining industries demand for better surface finish and accuracy has been increasing rapidly in recent years. Therefore, this paper focus on an effective approach for the optimization of process parameters in Minimum Quantity Lubrication (MQL) turning of AISI 4340 with nano fluid by using Grey Relational Analysis (GRA). Sixty experimental trials based on full factorial design matrix were carried on CNC turning lathe machine to optimize best level. Analysis of experimental results for response variable such as surface roughness and cutting force was performed using Grey Relational Grade (GRG). From GRA the optimal conditions are obtained as cutting speed (75 m/min), Feed (0.04 mm/rev), Depth of cut (0.5 mm) and Tool nose radius (0.8 mm) for optimal response variable surface roughness (1.26 μm) and cutting force (7.69 kgf). The Signal to Noise ratio plot for GRA shows similar optimum condition therefore the results obtained from ANOVA are closely matching to the results of GRA. Improvement in GRG is near about 4.32%. By analysing the GRG, it is observed that the cutting performance in MQL turning of AISI 4340 under MQL mode can be improved.