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Optimization and Prediction of Tribological Behaviour of Al‐Fe‐Si Alloy‐Based Nanograin‐Refined Composites Using Taguchi with Response Surface Methodology

S. Balaji, P. Maniarasan, S.V. Alagarsamy, Abdullah M. Alswieleh, V. Mohanavel, M. Ravichandran, Byong‐Hun Jeon, Haiter Lenin Allasi

2022Journal of Nanomaterials19 citationsDOIOpen Access PDF

Abstract

Aluminium matrix composites (AMCs) are broadly used to change the monolithic materials in aviation, automotive, and defense industries owing to their superior characteristics such as specific strength with light weight, greater hardness, good wear resistance, and better thermal properties. This novel work was aimed at estimating the specific wear rate (SWR) of zirconium dioxide‐ (ZrO 2 ‐) filled AA8011 (Al‐Fe‐Si alloy) matrix composites. A Taguchi method and response surface methodology (RSM) were used to find out the optimum range of control parameters on SWR of proposed composites. The stir casting technique was used to fabricate the composite specimens with varying proportions (5, 10, and 15 wt.%) of ZrO 2 particle addition. The wear tests were performed as per L27 orthogonal design by using a pin‐on‐disk apparatus under dry conditions. For this test, four control parameters such as wt.% of ZrO 2 , load, disc velocity, and sliding distance each at three levels were selected. Based on the experimental results, 15 wt.% of ZrO 2 , 29.43 N of load, 0.94 m/s of disc velocity, and 1000 m of sliding distance provide the minimum SWR of the developed composite sample. ANOVA result revealed that the load (49.04%) was the primary dominant factor for affecting the SWR, followed by wt.% of ZrO 2 content (29.24%), respectively. Moreover, scanning electron microscopy (SEM) analysis was performed to study the wear mechanism of worn‐out surface of the composite test specimens.

Topics & Concepts

Materials scienceTaguchi methodsComposite materialOrthogonal arrayComposite numberTribologyAlloyResponse surface methodologyScanning electron microscopeMetal matrix compositeAluminiumMachine learningComputer scienceAluminum Alloys Composites PropertiesMagnesium Alloys: Properties and ApplicationsAluminum Alloy Microstructure Properties
Optimization and Prediction of Tribological Behaviour of Al‐Fe‐Si Alloy‐Based Nanograin‐Refined Composites Using Taguchi with Response Surface Methodology | Litcius