Experimental Investigation of Cutting Parameters on Surface Roughness Prediction during End Milling of Aluminium 6061 under MQL (Minimum Quantity Lubrication)

This work investigates the effect of cutting parameters such as cutting feed, depth of cut and spindle speed on end milling of 6061aluminium so as to predict the surface roughness. One hundred and twenty experiments were carried out on aluminum 6061 rectangular rods. The experiments were conducted in dry and MQL environments using Mac-power V-645 CNC machine with HSS cutting tool inserts where five spindle speeds (700, 1500, 2000, 3000 and 4000rpm), four cutting feeds (120, 200, 500 and 1000mm/min) and three depths of cut (0.4, 0.8 and 1.0mm) were selected. The surface roughness obtained from each experiment was measured using Mitutoyo surface tester. Response surface methodology (RSM) was employed in the experimental design using Design Expert 8.0.1. Two mathematical models were developed; one for dry and the other for MQL machining using multiple regression analysis which can be applied to surface roughness prediction of end milling of aluminium under dry and MQL environments; analysis of variance (ANOVA) was used to determine the significance of cutting parameters on surface roughness. The results obtained show that cutting feeds have the most significant effect on surface roughness, followed by spindle speed; depth of cut has the least effect on surface roughness. The results also show that machining under MQL environment apart from being environmentally friendly reduced the surface roughness value to about 20% leading to a better surface finish. It was also observed that combination of cutting feed and spindle speed have the best interaction, followed by spindle speed and depth of cut. Cutting feed and depth of cut combination have the least interaction, leading to a poor surface finish.