An investigation on dry sliding wear behavior of aluminum based metal matrix composites using grey relational analysis coupled with principle component analysis

Abstract

 The current study reports on wear properties of aluminum 6061-T6 reinforced with titanium carbide and graphite hybrid metal matrix composite using principal component analysis based grey relational analysis. Experiments were carried out using Taguchi's L9 orthogonal array. The dry sliding wear properties of composite samples are evaluated using a Pin-on-Disc apparatus. The effects of wear parameter input variables such as load, sliding speed, and sliding distance on different output responses, namely wear rate, friction force, and coefficient of friction, were investigated in this work. Using grey relational analysis in conjunction with principal component analysis, three output responses from each experiment were normalized into a weighted grey relational grade. According to the analysis of variance, the most influential parameter is sliding velocity (45.51%), followed by load (26.75%) and sliding distance (2.94%), all of which contribute to the quality characteristics. Additional experiments have confirmed optimal results. Finally, a scanning electron microscopic analysis was performed to investigate the wear mechanism.