Investigation of the wear resistance and microstructure of Al/SiC metal matrix composites as a function of reinforcement volume fraction and reinforcement to matrix particle size ratio applying artificial neural network

Abstract

Abstract In this study, the influences of reinforcement volume fraction and the ratio of the reinforcement particle size to the matrix particle size on the wear behaviour of Al/SiC metal matrix composites were investigated by use of a model function obtained from an artificial neural network. Hardness and ball-on-disc wear tests were applied to Al/SiC composites manufactured via a powder metallurgy method. The results indicate that as the reinforcement volume fraction and the ratio of the reinforcement particle size to the matrix particle size increase, the wear loss decreases except in two cases; in the first case (vol.% ≤ 7.5), as the ratio of the reinforcement particle size to the matrix particle size rises, the wear loss increases and then decreases. In the second case, the decreasing trend of wear loss at high values of volume fraction (≥ 15%) declines and then increases where the value of the reinforcement to the matrix particle size ratio is about 1.