Multi-criteria Optimization for Wear and Friction Properties of Self-Lubricating Al6082-T₆/GNP/TiB₂ Hybrid Composites

The current work examines how wear-tribometer processing variables affect the wear and friction properties of self-lubricating Al6082-T₆/GNP/TiB₂ hybrid composites. The composites have been made using a UT-assisted bottom-pouring stir-casting route. The trails were set up by using RSM: Box–Behnken-Design (BBD), with reinforcement wt%, Normal-load (N), sliding velocity (V_s), and sliding distance (L) as input variables at three levels each. The entropy approach and TOPSIS were used to optimize numerous output responses, including volume-wear-loss (V), wear-rate (W_s), and coefficient-of-friction (μ). The entropy-TOPSIS technique found that the ideal combination of process parameters for attaining improved wear multiple responses concurrently was achieved at 8% (0.5% GNP + 7.5% TiB₂) reinforcement content, 30 N normal load, 1.79 m/s sliding velocity, and 310.1 m sliding distance. Taguchi, RSM, and ANOVA experiments revealed that reinforcement wt% is the most significant factor contributing (F = 127.34, P = 0.000) to enhancing wear performance attributes simultaneously. SEM investigations confirmed several wear mechanisms such as ploughing, debris, and abrasion on composite worn surfaces.