Multi-scale wear analysis of HRS/CNT hybrid polymer composites using predictive statistical modelling techniques

This study investigates the mechanical properties of Hibiscus Rosa-Sinensis/carbon nanotube (CNT) hybrid polymer composites, aiming to optimize specific wear rate and worn surface hardness under varying applied loads, rotational speeds, and CNT weight percentages. ANOVA statistical analysis revealed that the CNT weight percentage is the most critical factor, accounting for over 55% of the variation in both wear rate and hardness. Scanning Electron Microscopy confirmed that a 3 wt.% CNT composition provides the highest wear resistance and surface integrity across all tested loads. Furthermore, Response Surface Methodology (RSM) accurately predicted these wear behaviors, showing average errors of less than 3% for specific wear rate and under 7% for worn surface hardness. By utilizing desirability function analysis, this research provides a highly reliable framework for optimizing hybrid composites, paving the way for advanced materials that meet industrial demands for durability and performance.