Parametric optimization of the aluminium nanocomposites wear rate

Abstract

The optimization of wear rate of the nanocomposites with A356 aluminium alloy matrix, reinforced with silicon carbide nanoparticles, was performed through the analysis of the following influences: wt% of the reinforcement, normal load and sliding speed. The nanocomposites were produced by the compocasting process with mechanical alloying preprocessing (ball milling). Three different amounts of SiC nanoparticles, with the same average size of 50nm, were used as reinforcement, i.e. 0.2, 0.3 and 0.5 wt%. Tribological tests were performed on block-on-disc tribometer (line contact) under lubricated sliding conditions, at two sliding speeds (0.25 and 1m/s), two normal loads (40 and 100N) and at sliding distance of 1000m. Analysis of variance (ANOVA) was applied to determine the influence of different parameters on wear value of tested nanocomposites. It was noticed from ANOVA analysis that normal load, with 33.39%, is the most significant factor affecting the wear rate of nanocomposites. The amount of reinforcement, with 28.90%, also has a significant influence on the wear rate, while the influence of sliding speed, with 23.82%, is smaller. It was found that the prediction of wear rate, by using regression model and Taguchi analysis, were close to the experimental values.