Multi Objective Parameter Optimization of End Milling Operation on AA5083

Abstract

Aluminum alloys have many applications in modern engineering structure due to its high strength to weight ratio and high corrosion resistant nature. In most of the metal cutting industries, milling is generally used machining operation.For every machining process surface roughness can be taken as one of the quality measures. In this Taguchi based Grey relation analysis is used to investigate the machining characteristics of Aluminium alloy 5083. End milling operations performed on the basis of L9 Taguchi Orthogonal Array for various combinations of input parameters such as machine spindle speed, feed rate and depth of cut(DOC). The material removal rate(MRR) and surface roughness values are calculated for each experiment. The combinations are optimized by taking multiple responses such as Surface roughness and material removal rate. The optimum combination has been found out on the basis of grey relation grade. The optimum combinations obtained are the Spindle speed 1500 rpm, feed rate 350 mm/min and doc 0.2 mm. By analyzing ANOVA results depth of cut is most influencing input parameters as concerned to the multi objective optimization. From Taguchi analysis results most influencing parameter for the Surface roughness, material removal rate and combined result of both were found out. Regression model for the Surface roughness and is also created on basis of experimental results.