Effect of Graphite Addition on Mechanical Properties and Elevated Temperature Tribological Behaviour of Aluminium Zinc Alloy

Abstract

The objective of this experimental work was to study the sliding wear behavior of aluminum-zinc alloy based metal matrix composite (MMC) reinforced with the varying weight percentage of graphite particulate (1, 3 and 5wt%). The composites were manufactured using stir casting technique. The sliding wear studies of the fabricated composites have been conducted as per Taguchi’s L27 orthogonal arrays at different sliding speed (1.05-3.14 m/s), applied Pressure (0.37-1.14MPa), temperatures (30-900C) and fixed sliding distance (2000m) using a pin on disc tribometer. The microstructure examination of the worn out surfaces of composites specimens was carried out using a scanning electron microscope (SEM). As wear is a complicated phenomenon, an artificial neural network (ANN) technique was used for better prediction of the wear behavior of composites. The analysis of variance (ANOVA) and signal to noise ratio indicate that the temperature is most responsible control factor for the wear loss of composite specimen, followed by the load, speed and reinforcement. The minimum wear was observed for the composite with 3% reinforcement of graphite and least value of temperature, load, sliding speed. The correlation between response and control factor is obtained by multiple regression analysis using MINITAB software. The experimental wear results are matches with the wear results obtained from predictive Taguchi’s model and ANN model. Less worn out surface and shallow grooves were observed in the composites with 3% reinforcement of graphite.

Keywords: Composite, Stir casting, Scanning electron microscope, artificial neural network, MINITAB, Sliding wear, Taguchi orthogonal array