Application of Taguchi Methods and Regression Analysis to Optimize Process Parameters and Reinforcements for Maximizing Composite’s Coefficient of Friction for Brake Disc Application: A Statistical Optimization Approach

Abstract

for Al-CA-PB composites, with a focus on optimizing the coefficient of friction of the composite for brake disc production. The pumice, coal ash, and aluminum alloy were characterized using X-ray fluorescence (XRF), X-ray diffraction (XRD), thermogravimetric analysis (TGA), and scanning electron microscopy (SEM). The Taguchi method was employed to design the experimental runs and to identify optimal process parameters and reinforcements for maximizing the composite's coefficient of friction. At the same time, regression analysis was utilized to establish a robust mathematical model for predicting the composite's coefficient of friction based on the process variables. The XRF characterization results revealed that aluminum alloy contained Al, Si, and Mg as the major elements. The analysis also shows that the predominant constituents in coal ash were Si, Al, Fe, Ti, and Ca, whereas that of brown pumice particulates were Si, Fe, Al, Ca, K, and Ti. The XRD characterization analysis revealed that brown pumice and coal ash consist of SiO₂, Fe₂O₃, and Al₂O₃ as the major phases, making them well-suited as reinforcement in metal matrixes. According to the thermogravimetric and differential thermal analyses, the aluminum alloy, brown pumice, and coal ash have an onset temperature of 264.08, 724 °C, and 606.61°C, respectively, before deterioration. The optimal composite's coefficient of friction of 0.661 (experimental) was achieved at 2.5vol% of brown pumice, 10 vol% of coal ash, 400 rpm stirrer speed, 700 °C pouring temperature, and 15 minutes stirring duration. The developed mathematical model shows an excellent level of coefficient of friction prediction, with an R-squared value of 99.42%, 97.82%, and 76.40% for R-square, adjusted R-square, and predicted R-square, respectively.