Effect of turning environments and parameters on surface integrity of AA6061-T6: experimental analysis, predictive model
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ORIGINAL ARTICLE
Effect of turning environments and parameters on surface integrity of AA6061-T6: experimental analysis, predictive modeling, and multi-criteria optimization Mahshad Javidikia 1 & Morteza Sadeghifar 1 & Victor Songmene 1 & Mohammad Jahazi 1 Received: 17 June 2020 / Accepted: 31 August 2020 # Springer-Verlag London Ltd., part of Springer Nature 2020
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 multiobjective 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. Keywords Turning environment and parameters . Surface integrity . Regression model . Multi-criteria optimization . Aluminum alloy
1 Introduction Machining processes are commonly used in the aerospace industry to produce the final shape of the parts. Turning operations affect the surface integrity of machined components due to high temperature, large strain, and high strain rate occurring during cutting process [1]. It is important to improve the machining-induced surface integrity of surface and subsurface layers for crack prevention and fatigue life improvement [2, 3]. In a turning process, it is important to use optimum turning parameters (cutting speed, feed rate, and depth
* Mahshad Javidikia [email protected]; [email protected] 1
Department of Mechanical Engineering, École de Technologie Supérieure, Montreal, QC, Canada
of cut) and turning environment to achieve higher surface quality. The process could be carried out under dry, wet, or MQL modes, which the amount of cutting fluid applied in MQL machining is extremely smaller than that in wet machining. Cutting fluids as coolant and/or lubricant are utilized to reduce the generated heat
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