Multiobjective Optimization in Micromachining of Aluminum (Al 7075) using Taguchi Technique

In present scenario, the demand for precise micro components in the field of aerospace, mechanical, optics, electronics and biotechnology is increasing. This current work aims for optimization in micromilling of Al 7075 material using Taguchi robust technique. This work is carried out under three stages; experimental work, modelling and multiobjective optimization. Initially, micromilling experiments are carried out by constructing taguchi L9 orthogonal array keeping spindle speed, feed rate and depth of cut as controlled process variables, while results are analyzed using MINITAB 15 software for the responses Metal removing rate and Surface roughness. Regression Model replicating MRR and Surface roughness is created. To optimize all responses, Taguchi signal to noise ratio is used. Finally, analysis of variance (ANOVA) is done and multiobjective optimization results are predicted. It was found that for the optimized conditions of MRR and surface roughness spindle speed should be kept 2600 rpm, feed rate 600 mm/min and depth of cut should be in the range of 0.07 mm. From ANOVA it can be anticipated that feed rate is the most influencing factor which contributes 65% followed by spindle speed 18% and depth of cut 10%. It can be said that metal removing rate is adversely affected by feed rate while surface roughness is influenced by spindle speed.