Aluminum (Al) alloys are reinforced with carbides and oxides to enhance their properties. Al composites are developed to meet current automotive, shipbuilding, and aviation requirements. In the current study, aluminum 6061 is reinforced with B4C and Cr2O3 separately to fabricate Al6061 + B4C and Al 6061+Cr2O3 aluminum metal matrix composites (Al MMC). The Al composites were fabricated by stir casting with a wt % in steps of 2%, 4%, and 6%. Joining of Al MMC is essential to develop valuable components. The developed composites were welded using friction stir welding (FSW). FSW is recognized and widely used for joining Al MMC due to premium weld quality with minimum defects. The present study aims to analyze the effect of process parameters and predictive accuracy of the artificial neural network (ANN) and response surface methodology (RSM). The parameters selected for the study are tool rotational speed, tool travel speed, and reinforcement wt %. The FSW was performed based on the experimental design developed by the design expert software. Through RSM analysis, it was found that both the independent factors (tool rotational and tool transverse speed) and the interaction of factors jointly contribute to the FSW joint properties. The higher ultimate strength of 139 MPa and lower tensile strength of 48 MPa are found. As the tool travel speed increase from 20 to 25 mm\min, ultimate tensile strength increase about 59%. The average accuracy of RSM was 98.26 and of ANN was 94.86.

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The current study investigates the exfoliation corrosion behavior of friction stir welded aluminum composite. The stir casting method was employed to fabricate chromium oxide (2 and 4% wt) reinforced Al 6061 composites. The fabricated composite samples are friction stir welded with two process parameters. The solution immersion tests were performed for two intervals per the ASTM G34 (24 hours, 48 hours), and the weight loss method was employed. The corrosion sample is analyzed by optical microscope FESEM and surface roughness. The gelatinous corrosion product formed over the surface can apply pressure over the grains resulting in the formation of pits. The intergranular corrosion (IGC) is formed by continuous penetration of the solution and the pits. The grains suffering from IGC are more susceptible to pit. The weight-loss method is not sufficient to predict the damage induced by the exco solution. Evaluating the pit depth can help to know the severity of corrosion. The measurement of the pit is difficult due to its irregular nature. The surface roughness instrument is used, and the damage is represented in average roughness (Ra) and average depth (Rz). The exposure duration and welding parameters play a significant role in corrosion. More material is lost at higher process parameters and extended hours of the test, forming higher surface deterioration.