Stir Casting Process Analysis and Optimization for Better Properties in Al-MWCNT-GR-Based Hybrid Composites

Pure aluminium poses inferior properties that limit its use in load-bearing applications. Reinforcing multiwall carbon nano-tube (solid lubricant) and graphene to matrix offers better (antifriction, hardness, wear resistance) composites for such A stir casting processing route is employed prepare the hybrid composite (aluminium-multiwall nanotube-graphene Al-MWCNT-GR). The Taguchi L16 experimental representing four variables (percent reinforcement of graphene, die temperature, melt speed) operating at levels were studied analyze obtain higher hardness low rate composites. Percent showed maximum impact, temperature resulted with least contribution towards both responses. Criteria importance through intercriteria correlation (CRITIC) method applied determine weight fractions (importance) equal 0.4752 0.5482, respectively. Grey relational analysis (GRA) multi-objective optimization by ratio (MOORA) converts multiple objective functions into a single function assigned each output. Taguchi-CRITIC-MOORA outperformed Taguchi-CRITIC-GRA method, which could result 31.77% increase 36.33% decrease compared initial conditions. optimal conditions ensure dense microstructure minimal pores, enhanced obtained average worn-out surface results few thin slender grooves between tracks less crack propagation, ensuring self-lubrication fabricated optimized condition. correspond can be implemented industries large-scale