Determination of prediction model and optimization of process parameters for fabrication of Al-SiC composite using response surface methodology

Abstract

ABSTRACT The study attempted to optimise the fabricating process parameters for Aluminium silicon carbide (Al-SiC) metal matrix composites (MMCs) in a centrifugal casting machine. The effects of centrifugal casting die speed, melting temperature, the wt.% of reinforcement, and particle size were investigated experimentally based on wear performance and coefficient of friction (CoF). The wt.% of reinforcement (SiC) varied from 10% to 20% and particle size from 40 to 100 µm. While the die speed and melting temperature varied from 800 to 1200 RPM and 800 to 900°C respectively. Experiments were performed according to the central composite design model. For optimisation and investigation of individual and interaction effect of each variable on wear loss, and CoF response surface methodology tool was used. The statistical study of experimental results showed that reinforcement wt.% is the most influential factor on wear, followed by die speed, particle size, and melting temperature, respectively. The increased wt.% of reinforcement, die speed, and particle size results in decreased wear loss. At the same time, the effect of melting temperature on wear loss was also observed. The effect of melting temperature on wear and CoF was the least, and an increase in melting temperature increases the wear loss, while particle size was the second most influential factor found after reinforcement wt.% on CoF. Abbreviations: MMCs Metal Matrix Composites PMCs Polymer Matrix Composites CMCs Ceramic Matrix Composites D.O.E. Design of Experiment FGMMC Functional Grade Metal Matrix Composites CoF Coefficient of FrictionCCD Central Composite Design RSM Response Surface Methodology ANN Artificial Neural Network GRA Grey Relational Analysis ASTM American Society for Testing and Materials ANOVA analysis of variance Al-SiC Aluminium Silicon Carbide