Evaluation and Performance Improvement of Environmentally Friendly Sustainable Turning of 6063 Aluminum Alloy in Dry Conditions Using Grey Relational Analysis

Abstract

Sustainable machining has gained importance in recent years due to its environmental, economic, and societal implications. Aluminium (Al) 6063 alloy involves turning operation to make it suitable for various applications. The work's novelty is assessing the machining characteristics along with sustainability indicators. This study aims to find the best-turning parameters for machining Al 6063 alloy. The turning parameters considered were cutting speed, feed rate, and depth of cut. A cutting speed of 200 m/min, feed rate of 0.05 mm/rev, and depth of cut of 0.25 mm were the best parameter combinations for achieving a good machining response. From the response value of mean grey relational grade (GRG) and analysis of variance (ANOVA), the depth of cut ranks one with 34.38%, which is the most dominating parameter in achieving the sustainable machining of Al 6063 alloy. Through grey relational analysis, optimized machining parameters resulted in a 72.84 percent reduction in carbon emissions, 72.82 percent reduction in energy consumption, 18.58 percent reduction in cutting power, and 6.83 percent reduction in surface roughness considering the initial parameter settings and best machining parameters. The enhancement in total GRG was 0.1702, indicating improvement in the desired responses. As a result of this study, it is clear that appropriate machining parameter selection aids sustainable machining of Al 6063 alloy.