Optimizing the Wear Behaviour of AA7178 Metal Matrix Composites Reinforced with SiC and TiO2 Nanoparticles: A Comparative Study Using Evolutionary and Statistical Methods.

This work compares evolutionary and statistical strategies for improving the wear behaviour of AA7178 metal matrix composites reinforced with SiC and TiO₂ nanoparticles. The stir casting process was used to make the composites, and a pin-on-disc device was used in order to investigate the wear behaviour of the materials. The examination carried out using a scanning electron microscope (SEM) demonstrated that the reinforcement particles were distributed consistently over the surface of the aluminium matrix. Studies conducted using electron backscatter diffraction (EBSD) demonstrated that the incorporation of nanoparticles into composites brought to a finer grain structure in the finished product. The Taguchi technique and the particle swarm optimization (P.S.O) algorithm were used in order to optimize the data and conduct an in-depth analysis of the wear behaviour of the composites in comparison to the base alloy. The results showed that the sliding distance, applied load, and speed had the greatest impact on the wear rate for the base alloy matrix, AA7178 with 3wt.% TiO₂ and AA7178 with 3wt.% SiC nanocomposite, respectively. The tribological properties of the composites were significantly enhanced when nanoparticles of silicon carbide and titanium dioxide were included into the material. [ABSTRACT FROM AUTHOR]