Optimization of hybrid ZA‐27 nanocomposites using ANOVA and ANN analysis

Abstract

Nanocomposites based on graphite and aluminium oxide were synthesized via hot pressing process with pre processing mechanical milling. Optimization of wear loss and coefficient of friction of the nanocomposites with ZA 27 alloy matrix, was performed through the analysis of the following influences: sliding speed (100, 150, 200, 250 rpm), reinforcement of Gr (1, 2, 3, 4 vol.%) and reinforcement Al2O3 (1, 2, 3, 4 vol.%). Percentual influence of factors on wear loss and coefficient offriction was determined by ANOVA analysis and is as follows: sliding speed 10.05% and 0.61%,reinforcement of Gr 30.30% and 19.37%, reinforcement of Al2O3 52.99% and 69.01%, respectively. Validation of results using Artificial Neural Network (ANN) gave good correlation with experimental results. Based on this research, it can be observed that nanocomposites with reinforcement of Gr andAl2O3 can be potentially employed in many industries as a good substitute for the base alloy.