A combined approach to grey relational analysis and principal component analysis for development of input parameters in the wear characterization of Al7075 (SiC+Al2O3) hybrid metal matrix composites

Abstract

The current research aims to study the e ect of mechanical stir casting on the Al7075-based lightweight alloy made of Al 2 O 3 and SiC at di erent times and speeds of the stirrer. As observed, the hybrid metal matrix improved the wear resistance of the composite material Al7075 (SiC+Al 2 O 3 ). Experimental designs were formulated using Taguchi's DoE and based on four levels and four parameters, L 16 OA was selected. Both Grey Relational Analysis (GRA) and Principle Component Analysis (PCA) were employed to calculate the matrix composition. In addition, Pin-On-Disc (POD) test was done to measure the wear resistance of the cast pins. Further, mechanical characterizations such as tensile, hardness, impact, density, and porosity were identi ed through testing. The optimum parameters in this study were SiC of 6%, Al 2 O 3 of 4%, stirrer time of 15 min, and stirrer speed of 600 rpm, which led to the low wear loss of 0.0034 g, superior micro hardness of 154.22 BHN, tensile strength of 443.61 MPa, and impact energy of 3 J. From the ANOVA results, the stirrer speed was the most in uential parameter among others with the share of 49.40%. The worn surfaces were identi ed through the Scanning Electron Microscope (SEM) and Energy Dispersive X-ray (EDX) analyses.