Statistical Analysis and Optimization of the Yield Strength and Hardness of Surface Composite Al7075/Al2O3 Produced by FSP via RSM and Desirability Approach

In order to improve the properties of aluminum and its alloys, some various approaches (e.g. reduction of grain size, addition of alloying elements and composite manufacturing) have been considered. Among all these processes, the use of solid-state processes such as the friction stir processing (FSP) is highly convenient to create surface composites at temperatures below the melting point. Therefore, in this research, considering the FSP’s ability as a thermo-mechanical process and its advantages in the production of surface composites, the Al7075 surface composites were produced using reinforcing particles (Al2O3) and based on the FSP process in accordance with the design of experiments (DOE) approach. So, the response surface methodology (RSM) was selected as the experiment design method and variable factors such as: tool rotational speed, tool feed rate, diameter of tool shoulder and size of reinforcing particles were determined as the input variables. Statistical analysis and optimization of those parameters which affect the mechanical properties (yield strength and hardness) of surface composite Al7075/Al2O3 were performed. The results of the ANOVA and regression analysis of the experimental data approved the accuracy of regression equations and showed that the linear, interactional and quadratic terms of the input variables affect the yield strength and hardness of the composite specimens. Also, the optimal condition of the input variables was determined using the desirability method. In addition to the high values of desirability function (0.835, 0.822, 0.764), it could be found that the procedure of optimization has well fulfilled the pre-determined targets. In addition, the optimal condition has been confirmed by implementing the verification test.

کلیدواژه ها:

Statistical analysis ، Optimization ، Mechanical properties ، Surface composite ، Friction stir processing