Optimal selection of process parameters to reduce vibration during end milling of Al 356/SiC metal matrix composite

Machining performance are strongly influenced by vibration which occurs due to the dynamic nature of machine tool structures. A self excited vibration commonly known as chatter is frequent debacle occurs during milling operations which cause worsening outcomes such as excessive tool wear, poor surface finish and reduced tool life. In this paper an effort has been tried to optimize the machining and geometrical parameters for reduced vibration using Taguchi method with grey relational analysis during end milling of Al356/SiC metal matrix composites. The twin channel piezoelectric accelerometer has been used to measure vibration. Acceleration amplitudes at two different positions, one in spindle and another in work piece holder have been recorded for each experiment. Analyses of variance (ANOVA) have been applied to find the prominent parameters and the optimal parameter combination for best average response and signal to noise (SIN) ratio. Grey relational analysis has been implemented to find the optimal permutation of machining and geometrical parameters by considering both responses (acceleration amplitude taken at two different positions) simultaneously. Confirmation tests established that the grey-based Taguchi method has been successful in optimizing the process parameter for reduced vibration.