Multi-response optimization of machining parameters on CNC Milling of EN 19 alloy steel with TiAlN coated milling cutter using GRA

For the success of the manufacturing organization finding the optimum balance between higher production rate and improved quality is most important. Productivity can be interpreted in terms of material removal rate in the machining processes and quality represents product characteristics as desired by the customers which will give competitive edge over the competitors. Both these criterions are conflicting but important for the success of the organization. This paper presents the study of the parameter optimization of end milling operation for EN19 alloy steel with multi-response criteria based on the Taguchi L9 orthogonal array with the grey relational analysis. Surface roughness and material removal rate are optimized with consideration of performance characteristics namely cutting speed, feed rate and depth of cut. A comparative study has been done with compressed air and oil as a coolant by using TiAlN PVD coated carbide end milling cutter tool. A grey relational grade obtained from the grey relational analysis is used to solve the end milling process with the multiple performance characteristics. Additionally, the analysis of variance (ANOVA) is to be applied to identify the most significant factor. Finally, confirmation tests are performed to make a comparison between the experimental results and developed model.