Optimization of machining parameters of aluminum alloy 6026-T9 under MQL-assisted turning process

Abstract

The lower lead time and increasing demand for good quality parts require the industries to produce the parts manufactured sustainably with higher precision, improved productivity, and low cost using new techniques. Minimum quantity lubricant (MQL) is one of these techniques, which is economical and eco-friendly. This paper deals with the analysis and multi-response optimization of cutting process parameters of Aluminum alloy 6026-T9 in MQL and dry conditions using an integrated approach of composite desirability function and criteria importance through inter-criteria (CRITIC). The cutting parameters considered for the study are cutting speed, feed rate, depth of cut, and positive rank angle, while the responses are surface roughness profile (Ra, Rq, Rz), tool life and material removal rate. The type of insert used was a tungsten carbide, while the coolant was minimum quantity lubricant (MQL) vegetable oil (olive oil) performed at 150mL/hr. Taguchi orthogonal array (L16) using sixteen experimental runs are designed for machining. Based on analysis of variance (ANOVA) it is identified that the most significant cutting process parameters for surface roughness profile (Ra, Rq, Rz) under both dry and MQL conditions are the feed rate, while for the tool life are cutting speed and feed rate and for material removal rate is cutting speed followed by depth of cut and feed rate. Under dry conditions the optimized levels obtained are cutting speed of 500m/min, the feed rate of 0.3mm/rev, depth of cut of 2mm, and positive rake angle of 15°. However for MQL condition are cutting speed of 500m/min, the feed rate of 0.4mm/rev, depth of cut of 2mm, and positive rake angle of 15°. Finally, the machined worked piece surface and inserts are morphologically characterized at different cutting parameters using scanning electron microscopy (SEM) and Energy Dispersive X-Ray Analysis (EDX).