Response Surface Methodology Optimization of Wear Rate Parameters in Metallic Alloys

Abstract

The optimization of wear rate parameters in metallic alloys using Response Surface Methodology (RSM) has been experimentally performed. The wear rate, a critical factor affecting the durability and performance of metallic components, served as the response parameter, while track diameter, sliding speed, and mass difference were considered as independent variables. The Central Composite Design (CCD) experimental method systematically explored the response surface and optimizes the wear rate. A mathematical model was developed, revealing a significant p-value of 0.043 in the ANOVA table, indicating the collective influence of the independent variables on wear rate at a significance level of 0.05. Furthermore, the model demonstrates a substantial explanatory power, with R-squared of 69.45% and adjusted R-squared of 51.95%. The p-value calculated to be 0.60 for the statistical Lack of fit indicated a satisfactory model. These findings highlight the effectiveness of RSM in optimizing the experimental input values and offer valuable insights for enhancing the durability and performance of metallic alloys in various industrial applications. The obtained result addresses the problem of uncertainty inherent in optimal levels of input parameters wear experimentation.

Keywords

• Response Surface Methodology (RSM)
• Central Composite Design (CCD)
• Wear rate
• ANOVA
• Optimization
• p-value