Waste-Derived Composite Selection for Sustainable Automotive Brake Friction Materials Using Novel MEREC-RAM Decision Framework

This study aims to identify the most suitable slag waste-filled polymer composite for automotive braking applications. It employs a hybrid multi-criteria decision-making (MCDM) model that integrates the “method based on the removal effects of criteria” (MEREC) and the “root assessment method” (RAM) method. Eight slag waste-filled polymer composites, evaluated using seven performance-defining criteria, were considered in the MCDM analysis. The performance evaluation criteria included the friction coefficient, wear, friction fluctuations, friction stability, fade-recovery aspects, and rise in disk temperature. The criteria were weighted through the MEREC approach, which identified fade% (0.2890) and wear (0.2829) as the most important attributes in the assessment. The RAM was employed to rank the alternatives and suggested that the composite alternative with 60 wt.% slag waste and 5 wt.% coir fiber proved to be the best composition for automotive braking applications. The results were validated using nine MCDM models and Spearman correlation coefficients, which showed that the ranking of alternatives was consistent and stable even when the normalization steps of MEREC were swapped. Statistical validation demonstrated a strong predictive accuracy (p < 0.05) with a strong correlation coefficient (>0.8) alongside a minimal mean absolute error. Furthermore, sensitivity analysis was performed by examining several weight situations to determine whether the priority weights influenced the ranking of the composite alternatives. The findings from both the correlation and sensitivity analyses confirm the proposed hybrid MEREC-RAM model’s consistency and effectiveness.