Energy-Efficient Manufacturing: MCDM Techniques for Sustainability-Driven Optimization in Machining for Power Systems

Integration of sustainability dimensions i.e., environmental, economic, and social remains a relevant domain across the fields and deserves to be investigated. Hence, this work optimizes turning process to improve sustainability aspect in terms of productivity, surface quality, cutting force, and floor noise level as performance criteria using two multi-criteria decision-making (MCDM) methods, namely COPRAS, and WASPAS for ranking alternatives and criteria weighting method, ENTROPY, for the weight evaluation. ENTROPY method utilized to determine the criteria weights of the outputs, results in values of 0.208772 for MRR, 0.258356 for Roughness, 0.266006 for Cutting Force, and 0.266866 for Noise Level. Out of the 27 alternatives having all possible combination of the all input parameters, i.e., speed (150,200, 250 m/min), depth of cut (0.1, 0.3, 0.5 mm), and feed (0.05, 0.25, 0.45 mm/rev.), the alternative 7, with cutting speed 250 m/min, depth of cut 0.5 mm, and feed 0.05 mm/rev, is identified as the least favorable. However, the 27th alternative, having values for speed 350 m/min, depth of cut 0.5 mm, and the feed movement 0.45 mm/rev, is determined to be the most optimal. Both methods identified the same optimal and worst alternatives, which validate the ranking pattern. Studies with data-driven decision-making can assist in enhancing the operational efficiency and sustainability for real-world machining setups and assist manufacturers about selecting optimal parameters based on multiple performance criteria