Limestone slurry powder (LSP) is one of the solid wastes generated from stone processing industry, used as reinforcing agent replaced conventional ceramic compounds in Aluminum Metal Matrix composites (AMCs) to increase mechanical and tribological properties. In this work aluminum (Al)-magnesium ( Mg)-silicon (Si) alloy is strengthened with addition of LSP to determining the tribological performance of Al-LSP composites are composed with 4, 8, 12 and 16 % weight ratio, and prepared via double stir casting. The tribological tests were conducted on Pin-on-disc Tester, and used to evaluate sliding wear rate (WR) and coefficient of friction (CF). The results indicate that, the wear rate increased with increase of applied load and sliding velocity, but decreased with increasing LSP. Wear mechanism is observed with increase of applied load and changing from abrasion wear to delamination wear. The dispersoids phase in sub-surfaces, worn-out surface and distribution of LSP in base material are examined by Scanning Electron Microscope (SEM) and optical microscope. Taguchi Orthogonal Array (L25) is considered to estimate an optimal response. Analysis of variance (ANOVA) revealed that the most influencing parameters are sliding distance and working load on WR and CF respectively.
An attempt is made on tribological performance of aluminium composite (Al-Mg-Si) reinforced with Limestone slurry waste powder (LSP). Aluminium Metal matrix composite (AMC) is prepared using LSP by varying from 4% wt to 16% wt. LSP with 12 %wt. is shown better wear performance as compared to others. The experiments are designed based on the Taguchi approach (L25). In this study, sliding velocity (V), % of LSP (R), sliding distance (D) and load (L) as input parameters, whereas wear rate (WR- mm3/Nm) and coefficient of friction (CF) are responses. In addition, multi-variables are transformed to a single grey relation analysis (GRA) variable. The multivariable wear behaviour responses are transformed into one single variable with a grey relation grade. Analysis of variance (ANOVA) has been performed to determine the contribution of each parameter with interaction effects of design variables. The experimental results specify that the performance of wear behaviour characteristics in the tribological process has been improved by using grey-fuzzy reasoning grade (GFRG).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.