Multi-variable optimization for surface roughness and micro-hardness in MQL assisted face milling of EN31 steel using Taguchi based grey relational analysis

In the course of this analysis Taguchi approach with grey relational test data was carried out to provide an appropriate set of processes to encourage surface roughness and micro-hardness of EN 31 alloy. The optimal surface roughness and micro hardness were achieved as per TGRA. In addition, the appropriate set of process parameters were calculated by grey relational degree to enhance the quality of surface. The variance analyses for grey relationship grades have shown that the feed rate is the most important factor that affects surface integrity in EN-31 milling. Finally, confirmation experiments which significantly improve several quality characteristics have demonstrated the optimal combination of process parameters. The results of the confirmatory experiment showed that Taguchi method is an effective method of evaluating the available grey relation analysis. The desired surface quality cutting parameters for the EN-31-alloy milling in the MQL condition. (C)2021 Elsevier Ltd. All rights reserved.