Multi-response Optimization using TGRA for End Milling of AISI H11 Steel Alloy Using Carbide End Mill

Abstract

Abstract The AISI H11 steel is an important material used for making tools & dies. Machining is a very important activity in manufacture of tools & dies where the surface finish and metal removal rate play a very vital role. This paper presents the influence of the cutting speed, feed rate and depth of cut in end milling onto the surface roughness (SR) and metal removal rate (MRR). The machining experiments have been carried out on CNC vertical milling machine. Taguchi grey relational analysis (TGRA) with standard L27 orthogonal array has been selected to investigate the connection for studying surface roughness and metal removal rate (MRR). Both the responses viz. surface roughness and material removal rate are assumed to have equal weightage (W1 = W2 = 0.5) considering general machining conditions. The model significance tests have been conducted using ANOVA to find out which factors are statistically significant. The percentage contribution of cutting speed, feed rate and depth of cut are 29.13 %, 40.93 % and 17.4 % respectively. Optimization has been carried out to get optimum combination of SR and MRR.