Process Optimization for Fabrication and Wear Characterization of Aluminium Based Metal Matrix Composites

Abstract

In comparison to unreinforced alloys, reinforced metal matrix composites have strong wear newlineresistance, isotropic characteristics, high specific strength, specific modulus, damping capacity, newlinelow manufacturing costs, and the ability to be formed using traditional metalworking techniques. newlineThe possibility of using particle reinforced Metal Matrix Composites (MMCs) extensively in the newlinedomains of automotive, transportation, aerospace, construction, and commercial applications has newlineconsequently attracted more attention. newlineIn this study, an attempt is made to optimize the fabrication process parameters for aluminum newlinecomposite development for higher wear resistance. Aluminium Metal Matrix Composites newline(AlMMCs) have been made using conventional stir casting technology for many years. The present newlinecomposites are fabricated using centrifugal casting technologies with some modification, matrix newlineas Al6063 with reinforcement Silicon Carbide (SiC) is used. Molten metal pouring temperature newlineduring fabrication, mould die speed of centrifugal casting machine, reinforcement weight newlinepercentage and particle size as factor and wear and CoF as response considered for study. The pinon- newlinedisc wear test rig was used to conduct the wear test on the specimens, which were produced in newlineaccordance with ASTM G99 standard. Response surface methodology (RSM) optimization newlinemethod is used to get optimized condition. Central composite design (CCD) is used to control the newlinenumber of experiments. Regression equation and ANOVA results obtained by MINITAB newlinesoftware. Artificial neural network (ANN) soft computing model is also made to predict the wear newlinerate and coefficient of friction on AlMMCs. Correlations are made between the values produced newlinefrom the RSM and ANN models and the experimental values, and the higher predicted results are newlinethen confirmed by confirmation test. Statistics are used to discuss how wear parameters affect the newlinewear. The worn-out surfaces were examined under a microscope, and the SEM image analysis newlineprovides an example of how parameters affect the wear