Prediction of tribology in (Mg2Si+TiB2)/A356 composites based on RSM method and correlative with topographical characteristics

Abstract

This work deals with the prediction of tribological performance in (Mg2Si+TiB2)/A356 composites. In this work, tribological properties are also correlated with topographical characteristics. The effect of several input factors such as load, sliding distance and TiB2 wt% on tribological characteristics of (Mg2Si+TiB2)/A356 composites was explored by Response Surface Methodology (RSM). Central composite design (CCD) with three input factors and three levels of variables in RSM was used to develop a statistical model. RSM suggests a quadratic model to express a mathematical relationship between input factors to assess wear rate and coefficient of friction (COF). Analysis of variance (ANOVA) was applied to investigate the influence of input factors on wear rate and COF and found that most significant variable that influences wear rate and COF is applied load followed by TiB2 wt% and sliding distance. The desirability function approach is applied to optimized input variables to minimize wear rate and COF. Optimum wear rate is noticed at input variables of 26 N load, 2766 m sliding distance and 3.36 wt% of TiB2 and optimum COF was observed at 29 N of load, 2233 m sliding distance and 1 wt% of TiB2. A confirmatory test was conducted to validate the developed model and observed that experimental results matched the predicted value with an error of less than 5%. SEM and AFM examined surface topography of wear surfaces to understand the wear mechanism and surface features at various input factors. Microstructural features were also examined under optical microscope and SEM, revealing that increased TiB2 content in hybrid composite refined primary Mg2Si and eutectic Mg2Si phase and resulted in increased hardness and improved tribological behaviour of hybrid composite.