Evaluation and Improvement of Greenness for Milling AL6061 Alloy through Life Cycle Assessment and Grey Relational Analysis

Modern manufacturing industries thrive on greenness, which means ensuring acceptable environmental impacts and required surface quality of the products during the manufacturing process. However, there is a conflict between surface quality and environmental performances in the milling process. The current research only considers energy consumption rather than total environmental impacts. In this respect, this research focuses on the multiobjective optimization of machining parameters for balancing the surface quality (i.e., surface roughness, Ra) and total environmental impact (TEI), which includes raw materials usage, energy consumption, and output pollutant emission during the milling of AL6061 alloy. First, life cycle assessment (LCA) of the milling process is used for evaluating the TEI. Then, multiobjective optimization is conducted using Grey Relational Analysis. The results indicated that the improvement of Ra and TEI can be achieved with higher cutting speed, higher depth, and wet conditions in milling. The optimization work showed that cutting speed of 165 m/min, feed rate of 0.28 mm/rev, depth of cut of 2 mm, and width of cut of 3 mm are the optimal combination among existing experiments. Compared to single objective optimization results, multiple responses (Ra and TEI) can be improved simultaneously.