OPTIMIZATION OF ZINC-BASED HYBRID NANOCOMPOSITES USING TAGUCHI GREY RELATION ANALYSIS

Abstract

Hybrid nanocomposites have wide application in many industries. Nanocomposites with base alloy ZA27 reinforced with Al2O3 and Gr are commonly used for bearing applications. Taguchi based Grey relational analysis (GRA) was applied for the multi response optimization of parameters of nanocomposite for improving the tribological characteristics. In this investigation considered parameters are load (10, 15, 20, 25 N), reinforcement content of Gr and Al2O3 (1, 2, 3, 4 vol.%), while time and speed are constant as 30 min and 100 rpm, respectively. ANOVA analysis was used to determine influence parameters on wear loss and coefficient of friction (CoF) of nanocomposite. It was observed that the most influential parameter on tribological characteristics of nanocomposites was reinforcement content of Al2O3. Combination of parameters for optimal tribological characteristics is A1B1C4 i.e. load of 10 N, reinforcement content of 1 vol.% Gr and reinforcement content of 4 vol.% Al2O3. Obtained nanocomposite has shown good tribological properties which lead to less wear loss and therefore expectedly longer life of the bearing in various segments of the automotive industry.