Optimization of Tribological Performance of hBN/AL2O3 Nanoparticles as Engine Oil Additives

• Main Authors: Abdullah, Muhammad Ilman Hakimi Chua, Amiruddin, Hilmi, tamaldin, noreffendy, Mat Nuri, Nur Rashid
• Format: Article
• Language: English
• Published: 2014
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utem.edu.my/id/eprint/10513/1/1569767329.pdf; http://eprints.utem.edu.my/id/eprint/10513/

The purpose of this study is to determine the optimal design parameters, and indicate which of these design parameters are statistically significant for obtaining a low Coefficient of Friction (COF) with hexagonal boron nitride (hBN) and alumina (Al2O3) nanoparticles, dispersed in conventional diesel engine oil (SAE 15W40). Design of Experiment (DOE) was constructed using the Taguchi method, which consists of L9 orthogonal arrays. Tribological testing was conducted using a four-ball tester according to ASTM standard D4172 procedures. From analysis of Signal-to-Noise (S/N) ratio and Analysis of Variance (ANOVA), COF and wear scar diameter reduced significantly by dispersing several concentrations of hBN nanoparticles in conventional diesel engine oil, compared to without nanoparticles and with Al2O3 nanoparticle additive. Contribution of 0.5 vol.% of hBN and 0.3 vol.% of oleic acid, as a surfactant, can be an optimal composition additive in conventional diesel engine oil, to obtain a lower COF. In addition, the predicted value of COF by utilizing the levels of the optimal design parameters (0.5 vol.% hBN, 0.3 vol.% surfactant), as made by the Taguchi optimization method, was consistent with the confirmation test (average value of COF = 0.07215), which fell within a 95% Confidence Interval (CI).