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

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-m...

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Main Authors: Mat Tahir, Noor Ayuma, Abdollah, Mohd Fadzli, Hasan, Rafidah, Amiruddin, Hilmi, Abdullah, Muhammad Ilman Hakimi Chua
Format: Article
Language:English
Published: Emerald Group Publishing Limited 2017
Subjects:
T Technology (General)
TA Engineering (General). Civil engineering (General)
Online Access:http://eprints.utem.edu.my/id/eprint/20816/2/ilt_fadzli2.pdf
http://eprints.utem.edu.my/id/eprint/20816/
https://www.emeraldinsight.com/doi/full/10.1108/ILT-02-2016-0031
https://doi.org/10.1108/ILT-02-2016-0031
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spelling my.utem.eprints.208162021-07-08T20:59:07Z http://eprints.utem.edu.my/id/eprint/20816/ Statistical Models For Predicting Wear And Friction Coefficient Of Palm Kernel Activated Carbon-Epoxy Composite Using The ANOVA Mat Tahir, Noor Ayuma Abdollah, Mohd Fadzli Hasan, Rafidah Amiruddin, Hilmi Abdullah, Muhammad Ilman Hakimi Chua T Technology (General) TA Engineering (General). Civil engineering (General) 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. Emerald Group Publishing Limited 2017 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/20816/2/ilt_fadzli2.pdf 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 https://www.emeraldinsight.com/doi/full/10.1108/ILT-02-2016-0031 https://doi.org/10.1108/ILT-02-2016-0031
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
topic T Technology (General)
TA Engineering (General). Civil engineering (General)
spellingShingle T Technology (General)
TA Engineering (General). Civil engineering (General)
Mat Tahir, Noor Ayuma
Abdollah, Mohd Fadzli
Hasan, Rafidah
Amiruddin, Hilmi
Abdullah, Muhammad Ilman Hakimi Chua
Statistical Models For Predicting Wear And Friction Coefficient Of Palm Kernel Activated Carbon-Epoxy Composite Using The ANOVA
description 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.
format Article
author Mat Tahir, Noor Ayuma
Abdollah, Mohd Fadzli
Hasan, Rafidah
Amiruddin, Hilmi
Abdullah, Muhammad Ilman Hakimi Chua
author_facet Mat Tahir, Noor Ayuma
Abdollah, Mohd Fadzli
Hasan, Rafidah
Amiruddin, Hilmi
Abdullah, Muhammad Ilman Hakimi Chua
author_sort Mat Tahir, Noor Ayuma
title Statistical Models For Predicting Wear And Friction Coefficient Of Palm Kernel Activated Carbon-Epoxy Composite Using The ANOVA
title_short Statistical Models For Predicting Wear And Friction Coefficient Of Palm Kernel Activated Carbon-Epoxy Composite Using The ANOVA
title_full Statistical Models For Predicting Wear And Friction Coefficient Of Palm Kernel Activated Carbon-Epoxy Composite Using The ANOVA
title_fullStr Statistical Models For Predicting Wear And Friction Coefficient Of Palm Kernel Activated Carbon-Epoxy Composite Using The ANOVA
title_full_unstemmed Statistical Models For Predicting Wear And Friction Coefficient Of Palm Kernel Activated Carbon-Epoxy Composite Using The ANOVA
title_sort statistical models for predicting wear and friction coefficient of palm kernel activated carbon-epoxy composite using the anova
publisher Emerald Group Publishing Limited
publishDate 2017
url http://eprints.utem.edu.my/id/eprint/20816/2/ilt_fadzli2.pdf
http://eprints.utem.edu.my/id/eprint/20816/
https://www.emeraldinsight.com/doi/full/10.1108/ILT-02-2016-0031
https://doi.org/10.1108/ILT-02-2016-0031
_version_ 1705060035404496896
score 13.211869

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