Nano-alumina reinforcement on AA 8079 acquired from waste aluminium food containers for altering microhardness and wear resistance

• Main Authors: T. Sathish, N. Sabarirajan, R. Saravanan
• Format: Article
• Language: English
• Published: Elsevier 2021-09-01
• Series: Journal of Materials Research and Technology
• Subjects: Waste food container; Wear; Microhardness; Nanocomposite; Al2O3; ANOVA
• Online Access: http://www.sciencedirect.com/science/article/pii/S2238785421007043

The recycling of waste is act of charity as it takes part of maintain environmental clean as well as offer balance in supply to meet the same or alternate use. Thin Aluminium sheets made food packaging items are usually ‘use and through’ and AA 8079 obtained by recycled them after use by stir-casting process. This research aims to investigate the control over hardness and wear resistant by reinforcing alumina nanoparticles at different wt% in such recovered AA 8079 by Sliding wear test and Vickers micro hardness test to identify the degree of variation in mechanical and tribological aspect of reinforcement effects. The results of wear test reveal that the highly influencing functional parameter is normal pressure or load on the surface on the rate of wear than usage. The increase of quantity of reinforcement increases the wear rate in experimental results and the same confirmed with probability graph and the surface plots used to graphically analyses the relationship between combinations of parameters on wear rate. The increase of reinforcement increases, the microhardness also improved the same was depicted with microhardness graph. The effect of reinforcement in altering micro defects generation also investigated with SEM analysis and found that increase of reinforcement increases the micro defects. Contribution of wear functional factors and optimized parameter for minimum wear found by ANOVA and Taguchi analysis respectively. Hence the alteration of wear and microhardness properties can be done by nanoparticle reinforcement and the developed regression equation can be used for prediction of wear rate.