Experimental Investigation and Analysis of Effect of Process Parameters on Surface Roughness of AISI 4340 during MQL Turning with Nano Fluid

The selection of cooling system and effective optimization of machining cutting parameters affects cost and production time of quality of machined work piece material. This research work represents an investigation on response parameters such as surface roughness and metal removal rate during MQL turning of AISI 4340 with nano fluid along with comparative analysis of different cooling systems. Three values of feed rate and depth of cut respectively were chosen to study the effect on surface roughness. As per Taguchi design L9 orthogonal array design matrix has been selected for conducting of experiments. The optimal conditions are obtained from Grey Relational Analysis (GRA) as Feed (0.04 mm/rev.) and Depth of cut (1.5 mm). The Signal to Noise ratio plot for GRA shows similar optimum condition therefore the results achieved from ANOVA are closely matching to the results of GRA. Improvement in grey relational grade is near about 1.24%. From the comparative result analysis, it was observed that Minimum Quantity Lubrication (MQL1) with nano fluid (MWCNT) showed lowest surface roughness compared to MQL2, dry and flood condition. Also it is found that the percentage error is below ±5%. For MQL1 at optimum condition (Feed rate 0.04 mm/rev. and Depth of cut 1.5 mm) the obtained surface roughness (R_a = 1.01μm). The findings of this study show that MQL with nano fluid can substitute the flood lubrication for better surface finish and performance characteristics can be improved effectively through this approach.