Optimization of machining parameters to minimize vibration amplitude while machining Al 6063 using gray-based Taguchi method

Abstract

Vibration during end milling causes a destructive effect: it produces poor surface finish, accelerates tool wear and reduces tool life. This article presents the use of Taguchi method–based gray relational analysis to optimize the machining parameters such as helix angle of cutting tool, cutting speed, feed rate, axial depth of cut and radial depth of cut for reduced vibration amplitude in end milling operation. L25 Taguchi orthogonal design was employed for conducting the experiments. The experiments were conducted on aluminum Al 6063 by high-speed steel end mill cutter, and acceleration amplitude was measured using fast Fourier transform analyzer. The online signals recorded for vibration amplitude picked by accelerometer at two positions: one fixed in the spindle (channel I) and another fixed in the workpiece fixture (channel II). Signal-to-noise ratio and analysis of variance were employed to determine the optimum levels. Gray relational grade was used to optimize machining parameters by considering both responses at a time.