Abstract

Applications of aluminum matrix composites are increasing in aerospace, automotive and biomedical fields because of their high strength, light weight and good wear resistant properties. From an intense literature review it is observed that various combinations of aluminum alloys have been developed through different manufacturing methodologies and their characteristics have been studied. It is identified that the study of a composite material consists of AA6061 alloy as a matrix material reinforced with SiC and B4C; a comparative experiment on sliding wear characteristics, hardness and wear resistant properties of nanocomposite with different aging time is a novel area yet to be undertaken. This paper presents a study of sliding wear characteristics in silicon carbide, boron carbide reinforcement prepared by using stir casting process. The hardness and wear resistance properties of nanocomposites with different aging time were measured in the work. When comparatively analyzed with AA6061, AA6061 reinforced with silicon carbide, AA6061 reinforced with boron carbide exhibited a steady and higher hardness than the other two metal composites. Also, we observed that when sliding wear characteristics are compared, the AMC reinforced with boron carbide exhibits an optimum wear rate. The optimal values of control parameters in wear rate and friction coefficient for boron carbide reinforced aluminum matrix composites are determined by response surface methodology. The control parameters considered are applied load, speed, weight % of reinforcement and distance. The effect of control parameters on the output variables was investigated by analysis of variance (ANOVA) and response plot. Interestingly, 27% increase in hardness value for B4C reinforced composite material at the aging time of 200 minutes was observed. Furthermore, wear rate for B4C reinforced composite material was four times reduced as compared to monolithic AA6061. These improvements may be attributed to the homogeneous particle size, particle distribution without agglomeration and optimized parameters.

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