Experimental investigation of machinability characteristics and multi-response optimization of end milling in aluminium composites using RSM based grey relational analysis

Abstract This paper investigates the machinability characteristics of end milling operation to yield the minimum surface roughness, cutting force, tool wear with the maximum material removal rate using RSM based grey relational analysis. Twenty-seven experimental runs based on Box-Behnken Design of Response Surface Methodology (RSM) were performed by varying the parameters of spindle speed, feed and depth of cut in different weight percentage of reinforcements such as Silicon Carbide (SiC-5%, 10%, 15%) and Alumina (Al 2 O 3 -5%) in aluminium 7075 metal matrix. Grey relational analysis was used to solve the multi-response optimization problem by changing the weightages for different responses as per the process requirements of quality or productivity. Optimal parameter settings obtained were verified through confirmatory experiments. Analysis of variance was performed to obtain the contribution of each parameter on the machinability characteristics. The result shows that spindle speed and weight percentage of SiC are the most significant factors which affect the machinability characteristics of hybrid composites. An appropriate selection of the input parameters (spindle speed of 1000 rpm, feed of 0.03 mm/rev, depth of cut of 1 mm and 5% of SiC) produces high material removal rate coupled with fine surface finish, less tool wear and low cutting force.