Abstract
The statistical design of experimental techniques has been widely explored in developing empirical methodologies. These methods are beneficial for developing appropriate mathematical models to predict the properties and performance of various materials. This study utilized the user-defined design (UDD) approach under response surface methodology (RSM) to achieve the optimum parameters for dry sliding wear properties of graphite-reinforced binderless TiC0.5N0.5 ceramic composites. The tribological tests were performed using a ball-on-flat geometry tribometer, with a ruby- TiC0.5N0.5 friction pair operating in sliding mode at ambient temperature. The developed mathematical model specifies the functional relationship between the key parameters, using the weight percentage of the graphite reinforcement and applied load as input variables and wear rate as the output variable. Based on the statistical analysis, ANOVA results for wear rate indicated that the predictability of the model is at 95 % confidence level. Moreover, the wear rate demonstrated a correlation coefficient of R2 = 0.9762, which depicts that only less than 3 % of the total variations are not explained by the model, and the value of the adjusted determination coefficient (adjusted R2 = 0.9366) is high, proving that the model is significant.