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Material selection of natural fibre using a stepwise regression model with error analysis


Citation

Noryani, Muhammad and Salit, Mohd Sapuan and Mastura, Mohammad Taha and Mohd Yusoff, Mohd Zuhri and Zainudin, Edi Syams (2019) Material selection of natural fibre using a stepwise regression model with error analysis. Journal of Materials Research and Technology, 8 (3). pp. 2865-2879. ISSN 2238-7854

Abstract

The nature of natural fibre such as it is lightweight, recyclable, biodegradable and gives a high performance in relation to its mechanical properties makes this material an excellent alternative to currently used materials in the manufacture of automotive components. The significant mechanical properties are identified using the best statistical model suggested by stepwise regression in this study. The estimation and error analysis of the response variables are discussed to select the best natural fibre for automotive component applications. The results using statistical measurement indicate that tensile strength is the most significant mechanical property for all the selected natural fibres. The final ranking that considered high performance score and minimum error analysis for a hand-brake lever application found that coir, kenaf and cotton are the top three candidates with average scores of 4, 4.5 and 5, respectively. The statistical model presented in this study can be used in multiple applications. In fact, this approach is helpful to the design engineer when huge amounts data are involved.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
Institute of Tropical Forestry and Forest Products
DOI Number: https://doi.org/10.1016/j.jmrt.2019.02.019
Publisher: Elsevier
Keywords: Material selection; Natural fibre; Stepwise regression; Error analysis
Depositing User: Ms. Nida Hidayati Ghazali
Date Deposited: 15 Jun 2021 10:03
Last Modified: 15 Jun 2021 10:03
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1016/j.jmrt.2019.02.019
URI: http://psasir.upm.edu.my/id/eprint/81294
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