Tribological Behavior of Al/Nanomagnesium/Aluminum Nitride Composite Synthesized through Liquid Metallurgy Technique

Abstract

Despite its excellent qualities such as hardness, tensile, and yield strength, aluminum alloys are mostly used in aviation fins and car frames. However, wear resistance at maximum load is weak. This effort will now synthesize and investigate the tribological behavior of AA6063‐ (AlMg0.7Si‐) AlN composites. The goal of this experiment is to determine the best wear rate and coefficient of friction for the AA6063‐AlN with nanomagnesium composites developed. Weight percent, load (L), sliding velocity (SV), and sliding distance (SD) are the process factors studied, and the output responses are wear rate and friction coefficient. Bottom pouring type stir casting was used to create AA6063‐AlN composites with various weight percentages. The various compositions are AA6063, AA6063‐4 wt% AlN, AA6063‐8 wt% AlN, and AA6063‐12 wt% AlN. A pin‐on‐disc machine inspected the wear rate and friction coefficient of AA6063‐AlN composites. Experimentation was done according to L16 orthogonal array (OA). Wear rate (WR) and coefficient of friction (COF) examinations were made to identify the optimum parameters to obtain minimum WR and COF for the AA6063‐AlN composite via grey relational analysis (GRA). The contour plot analysis clear displays WR and COF with respect to wt% vs. L, wt% vs. SV and wt% vs. SD. The ANOVA outcomes revealed that wt% is the most vital parameter (85.55%) persuading WR and COF. The optimized parameters to achieve minor WR and COF was found as 12 wt% of AlN, L 20 N, SV 3 m/s, and SD 400 m. The worn surface was analyzed using scanning electron microscope and indicates that addition of AlN particles with matrix reduces the scratches. These articles offer a key for optimum parameters on wear rate and COF of AA6063‐AlN composites via Taguchi grey relational analysis.