Investigation and Optimization of Tribological Properties of Hybrid Composites (Al6061/SiC/Graphene) using Taguchi Technique

The excellent mechanical characteristics of aluminum matrix composites reinforced with silicon carbide (SiC) are well known. Aiming to improve tribological performance under various loading conditions for demanding engineering applications, this work investigates the combined effect of incorporating different numbers of graphene nanoparticles into an Al-SiC matrix. Stir casting produced composites of an aluminum (Al 6061) matrix reinforced with 5 weight percent silicon carbide (SiC) and varying amounts of graphene (0%, 0.1%, and 0.3% by weight); their compositions were confirmed by Energy Dispersive X-ray Spectroscopy (EDX). At a constant speed of 300 RPM, tribological behavior was evaluated using pin-ondisc tests conducted under dry sliding conditions at weights of 20N, 30N, and 40N volume loss was identified as the main output parameter. The tribological performance was much enhanced by the graphene incorporation. When the Al-SiC matrix included 0.1 weight percent graphene, the coefficient of friction (COF) and volume loss dropped significantly under a 40N high load. The 0.3 wt.% graphene composite showed improved tribological characteristics in contrast to the 0.1 wt.% composite at reduced loads (20N and 30N), therefore demonstrating an ideal graphene concentration dependent on the load. The observed improvements are attributed to the formation of a self-lubricating, graphene-rich tribo-layer on the wear surface, which greatly reduces friction and abrasive wear. The substantial decreases in wear and coefficient of friction achieved with 0.1 weight percent graphene at 40 N. Improved performance of the 0.3 weight percent composite was observed under lower applied loads of 20 N and 30 N. The measurable influence of both the applied load (64.26%) and the graphene composition (20.16%) on the wear properties of the composites was achieved. The SiC particles provide the aluminium matrix with sufficient load-bearing capacity to support it concurrently. Especially in the 0.1 wt.% graphene composite, the study using Scanning Electron Microscopy (SEM) revealed a rather constant distribution of the reinforcements, which most likely contributed significantly to its enhanced performance. Apart from assessing the potential scalability in industrial applications, the next studies will focus on evaluating the long-term wear characteristics and fatigue resilience of the improved composite under more demanding operating conditions.