An investigation on dry sliding wear behavior of Al6061/ Titanium carbide/ Basalt hybrid metal matrix composites

Abstract

Dry sliding wear plays an important role in selecting material for automotive and aerospace applications. Researchers have been exploring novel aluminum matrix composites (AMC), which offer minimum wear rate for various tribological applications. The present work involves multi-objective optimization for dry sliding wear behavior of Al6061 reinforced with 6 % of Titanium carbide and 4% of basalt hybrid metal matrix composites using principal component analysis (PCA)-based grey relational analysis (GRA). In this article, the effects of input variables of wear parameters such as applied load, sliding speed and sliding distance were investigated on different output responses, namely the wear rate, friction force and specific wear rate. Taguchi’s L9 orthogonal array with three-level settings was chosen for conducting experiments. Three output responses in each experiment were normalized into a weighted grey relational grade using grey relational analysis coupled with the principal component analysis. The analysis of variance indicated that sliding distance is the most influential parameter followed by load and sliding velocity that contributes to the quality characteristics. Optimal results have been verified through additional experiments.

Keywords

• aluminum matrix composites
• taguchi method
• grey relational analysis
• principal component analysis
• anova