Manufacturing and Machining Performance Analysis of Al/SiC5 MMC using Soft Computing Techniques

Abstract

Now a day’s, metal matrix composites (MMCs) are taking a superior position among the available material. The presented work aims to investigate the ease of machining for Aluminium based MMC (AlSiC5- with 5% Silicate). These MMCs are extensively used in space, defence, automobile, etc. To analyze the process, an effective two techniques ie. Response surface method (RSM) & artificial neural networks (ANN) have been selected to analyze the process. Taguchi’s L₂₇ plan was used for data collection. The parameters like current (AMP) and pulse on time (TON) are the basically dominant parameters, followed by voltage (VOLT) and pulse off time (TOFF). The ease of machining performance measured in terms of surface roughness (Ra). From obtained result, it is seen that the ANN & RSM presents an exemplary commitment. An adequate contract was observed with the high correlation coefficient value (R2 = 0 9863) in RSM and (R2 = 0 9764).