Effect of turning environments and parameters on surface integrity of AA6061-T6: experimental analysis, predictive modeling, and multi-criteria optimization

Abstract

The present research investigates the effect of turning environments and parameters on surface integrity induced by turning of AA6061-T6. Specifically, the evolution of turning parameters of cutting speed, feed rate, and depth of cut was studied under dry, minimum quantity lubrication (MQL), and wet environments and their impact on surface roughness and residual stresses, as critical parameters for surface integrity, were quantified. Machining tests were carried out using a design of experiment (DoE) based on central composite design (CCD) under the three turning environments. The most effective turning parameters were identified for each environment using analysis of variance (ANOVA). Response surface method (RSM) was used to predict effective regression models for each turning environment for the average arithmetic surface roughness, the height peak from the valley, the axial surface residual stress, and the hoop surface residual stress. Then, using the predictive regression models, a multi-objective optimization study was performed to determine optimal turning parameters in each environment for improved surface integrity in low speed turning (LST) and high speed turning (HST) of AA6061-T6. The results showed that feed rate and cutting speed were the most effective parameters on surface integrity. It was also found that better surface integrity and higher material removal rate (MRR) were achieved using MQL mode, which is an environmental friendly and cost-saving turning environment.