Optimizing Wear Performance: Comprehensive Analysis of Aluminium 6061 Metal Matrix Composites Reinforced with Coconut Shell Ash and Graphene

This research systematically investigates the wear characteristics of aluminium 6061 metal matrix composites (MMC) incorporating coconut shell ash particulates (CSA) and graphene. The study initiates with a meticulous microstructural analysis to evaluate the size and composition of reinforcements. Fabrication of composites through stir casting involves a constant graphene percentage (0.6%) and incremental CSA variations from 0 to 8%. Employing Taguchi Design of Experiments (DOE) with an L16 array, the experimentation explores load, speed, track radius, and reinforcement percentage parameters. Analysis of variance (ANOVA) scrutinizes their effects on wear rate, wear loss, and COF responses. Preceding the optimization with response surface methodology (RSM), this analysis aims to unravel the collaborative impacts of CSA and graphene on Al6061 MMC. The study identifies optimal compositions for enhanced wear resistance across diverse mechanical applications. Results indicate that reinforcement significantly reduces specific wear rate (SWR), while load exerts substantial influence on wear loss. COF is primarily influenced by speed and reinforcement. The optimization solution suggests that at reinforcement = 8.6, load = 15.4545, speed = 200, and track radius = 40, the composite achieves a desirability of 0.874598. Multiple response predictions validate this solution, emphasizing the importance of considering all factors for optimal performance. The relative percentage errors for specific wear rate (12.37%), wear loss (14.28%), and COF (12.13%) demonstrate the reliability of the predictive models.