Multi-response optimization of machining parameters for end milling process on BSL168-T6511 aluminium alloy using Taguchi based grey relational analysis

Abstract This paper presents a novel approach for the optimization of machining parameters of end milling process with multiple responses, based on Taguchi’s orthogonal array (OA) and gray relational analysis (GRA). Experiments were conducted on BS L168-T6511 aluminum alloy test specimens with uncoated carbide solid end mills under dry condition. The cutting process parameters considered: cutting speed (S), feed rate (F) and depth of cut (D) are optimized for betterment of the multiple responses such as: surface roughness (Ra), cutting tool tip temperature rise (T) and material removal rate (MRR). A grey relational grade (GRG) is determined from the grey relational analysis (GRA). Optimum levels of process parameters have been identified based on the values of grey relational grade and influence of each cutting process parameter is determined by ANOVA. To validate the test results, confirmation tests are performed. Experimental outcomes have proved that the output responses in end milling process can be enhanced efficiently through this approach.