Statistical Models For Predicting Wear And Friction Coefficient Of Palm Kernel Activated Carbon-Epoxy Composite Using The ANOVA

Mat Tahir, Noor Ayuma and Abdollah, Mohd Fadzli and Hasan, Rafidah and Amiruddin, Hilmi and Abdullah, Muhammad Ilman Hakimi Chua (2017) Statistical Models For Predicting Wear And Friction Coefficient Of Palm Kernel Activated Carbon-Epoxy Composite Using The ANOVA. Industrial Lubrication And Tribology, 69 (5). pp. 761-767. ISSN 0036-8792

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Official URL: https://www.emeraldinsight.com/doi/full/10.1108/IL...

Abstract

Purpose – The purpose of this study was to propose statistical models for predicting wear and friction coefficient of the palm kernel activated carbon-epoxy composite using the analysis of variance (ANOVA). Design/methodology/approach – All the specimens were formed into 10-mm diameter pins of 30-mm length each. The tribological test was conducted using a pin-on-disc tribometer. The results of the coefficient of friction (COF) and the wear rate were then analysed using the ANOVA. Regression analysis was used to derive the predictive equations for both friction coefficient and wear rate. Findings – It was found that the most significant parameter that affects the COF is the weight composition, while for the wear rate, it is the operating temperature. The proposed statistical models have 90-94 per cent reliability. Research limitations/implications – The equation models are only limited within the tested parameters and ranges in the plastic deformation region. Originality/value – These models can be very useful for material design engineers in avoiding the component failures occurring prematurely.

Item Type:	Article
Uncontrolled Keywords:	Resins, Wear, Friction, Composite materials, Waste, Regression analysis
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Faculty of Mechanical Engineering
Depositing User:	Mohd Hannif Jamaludin
Date Deposited:	28 May 2018 07:41
Last Modified:	08 Jul 2021 20:59
URI:	http://eprints.utem.edu.my/id/eprint/20816
Statistic Details:	View Download Statistic

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