Assessment of mechanical and tribological performance of hybrid Al/MoS2/Al2O3 composite by GFRA

Abstract

This work emphasizes the mechanical and tribological performance of Al-Si/Al2O3/MoS2 hybrid matrix composites. The composites are reinforced by varying weight percentages of Al2O3 (8%, 12%, and 16%) and MoS2 (0%, 2%, and 4%), and were prepared by stir casting. As the weight percentage of Al2O3 in a composite grows, so does its hardness and tensile strength. The addition of 2% wt. MoS2 enhances the specific strength and tribological properties, according to the research. However, when compared to other composites studied, the Al/16% Al2O3 composite had improved mechanical properties. MoS2 also aids the hybrid composite in achieving higher tribological characteristics while marginally lowering the specific strength. Taguchi orthogonal array (L27) is used to design tribological performances with process parameters viz. applied load, sliding speed and weight % of Al2O3 as well the percentage of MoS2 whereas wear rate (mm3/m), wear (µm) and coefficient of friction were considered as the responses. A hybrid Grey–Fuzzy Reasoning Approach (GFRA) is used to optimize a multi-response for avoiding vagueness in decision making. The statistical analysis revealed that Al/2%MoS2/16%Al2O3 composite has exhibited better wear resistance than other composites. The confirmation test is also conducted to validate the optimal condition obtained by ANOVA.

A contrastive characterization of pure Mg and AZ91D alloy based on the testing of mechanical, corrosion, wear, and erosion properties

“…The average statistical level is the significance of S/N ratios at different parameterization levels. The response tables mean values are represented graphically is discussed with respect to the response graph illustrated [33,34]. A response comes under smaller the better category, the corresponding S/N ratio values are calculated using the equation (1).…”