Assessing Machine Tool Selection Process in Sustainable Production to Address Climate Change Based on Hybrid MCDM Methods

Abstract

In recent years, there has been an increasing focus on optimizing production processes with the concept of sustainability because of the awareness of climate change around the world. Meanwhile, the machine tool is a crucial component of the manufacturing process. Therefore, this research aims to evaluate the process of machine tool selection in production with a concentration on reducing carbon dioxide emissions. Through the integration of different Multi-Criteria Decision-Making (MCDM) methods, including the Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and Evaluation based on Distance from Average Solution (EDAS), a mathematical model is proposed to make the best choice for machine tools. According to the AHP method, the motor output of the main spindle holds the most significant weight in the evaluation criteria, making it the most important factor to consider. The selection of the ideal machine tool is determined through the TOPSIS and EDAS methods. After careful evaluation, the CKQ 6136 CNC lathe has been identified as the optimal choice, as it scored the highest assessment value in both TOPSIS and EDAS methods. This study contributes to environmentally responsible manufacturing practices by considering machine tool selection, sustainability, and climate change mitigation.