Entropy and EDAS-based multi-criteria decision-making approach to optimize CNC machining parameters

The aim of this study was to investigate the effectiveness of the Entropy and Evaluation Based on Distance from Average Solution (EDAS) method in selecting optimal machining parameters for achieving the lowest surface roughness and cutting power in Computer Numerical Control (CNC) router operations. The impact of critical machining parameters, including feed rate and spindle speed, was investigated for Scots pine, Oriental spruce, Anatolian chestnut, and Oriental beech. Based on the overall EDAS ranking, the optimum machining parameters were determined as follows: 22,000 rpm spindle speed and 2 m/min feed rate for beech, pine, and spruce, and 14,000 rpm spindle speed and 2 m/min feed rate for chestnut. It was stated that the results are promising, and Multi-Criteria Decision-Making Methods can contribute to the development of more efficient and effective CNC machining processes that can meet the specific requirements of different wood products and applications.