Statistical Analysis and Optimization of the Experimental Results on Performance of Green Aluminum-7075 Hybrid Composites

Abstract

The present study assessed the potential of engaging response surface analysis in the experimental design, modeling, and optimization of the strength performance of aluminum-7075 green composite. The design of the experiment was carried out via the Box–Behnken method and the independent variables are rice husk ash (RHA) at 3–12 wt.%, glass powder (GP) at 2–10 wt.%, and stirring temperature (ST) at 600–800 °C. Responses examined are yield, ultimate tensile, flexural, and impact strengths, as well as microhardness and compressive strength. ANOVA analysis revealed that the input factors had consequential contributions to each response, eventually presenting regression models statistically fit to represent the experimental data, further affirmed by the diagnostic plots. The result of the optimization envisaged an optimal combination at 7.2% RHA, 6.2 GP, and 695 °C with a desirability of 0.910. A comparison between the predicted values for the responses and the values of the validation experiment revealed an error of <5% for each response. Consequently, the models are certified adequate for response predictions at 95% confidence, and the optimum combination is adequate for the design of the composite.

Keywords

• AA-7075
• mechanical performance
• modeling and optimization
• statistics
• validation