Modeling and optimization of end milling parameters on aluminum 6061 alloy using GRA based Taguchi method coupled with PCA

Quality and productivity are two important aspects for manufacturing industries. Modeling and optimization is the best technique applied to find the best manufacturing conditions. This technique has been applied to investigate the optimized design of the cutting process in end milling for Al 6061 alloy in order to provide better surface finish as well as high Material Removal Rate (MRR). The cutting parameters considerd are coolant employment, spindle speed, feed, and depth of cut. The Al 6061 alloy has a wide variety of applications in automobile industries as well as aerospace industries due to its light weight to strength ratio, high corrosion resistance, heat treatable and easily weldable property. The experiments were conducted on L18 (2 1 ×3 3 ) orthogonal array, Analysis of Variance (ANOVA) was used to obtain individual optimization latter Grey Relational Analysis (GRA) based Taguchi method has been used for effective optimization. A Gray Relational grade found out by the GRA has been used to obtain the best end milling process parameters with multiple performance characteristics. In order to evaluate the weighting values corresponding to various performance characteristics, principle component analysis (PCA) has been used so that their relative importance can be objectively described. Graphs and response table were used to find the optimal levels of parameters in end milling process. Finally, a comparison between the experimental results and developed model was obtained using conformation tests. The machining performance in the end milling process can be improved effectively by applying this technique.