Predicting the ultimate tensile strength and wear rate of aluminium hybrid surface composites fabricated via friction stir processing using computational methods

In the present study, aluminium hybrid surface composites were prepared by incorporating boron carbide (B4C) and Aluminium oxide (Al2O3) ceramic particles via the Friction Stir Processing (FSP) route. Tool rotational speed, Tool traverse speed, Axial force, and Reinforcement ratio were the chosen process parameters. Response Surface Method (RSM) based Central Composite Design (CCD) was used to conduct the experimental trials. A second-order regression equation was developed for the responses, ultimate tensile strength (UTS), and wear rate (WR). Statistical tests were performed to check the adequacy of the regression models. The effect of process parameters on the responses was studied. It was found that tool traverse speed was the most dominant process parameter, followed by tool rotational speed, axial force, and reinforcement ratio. The optimal process parameters for the responses were found using a genetic algorithm, where the regression equations from RSM were used as the objective function.