Effect of alkali treatment conditions optimization on kenaf fiber polyester composite characterization

This study was conducted to evaluate the alkali treatment conditions optimization impact on kenaf fiber and its short random oriented kenaf fiber reinforced polyester matrix composite mechanical properties characterization. The selected treatment conditions are alkali solution concentration (2% w/v...

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Bibliographic Details
Main Author: Hashim, Mohd Yussni
Format: Thesis
Language:English
English
English
Published: 2016
Subjects:
Online Access:http://eprints.uthm.edu.my/820/1/24p%20MOHD%20YUSSNI%20HASHIM.pdf
http://eprints.uthm.edu.my/820/2/MOHD%20YUSSNI%20HASHIM%20COPYRIGHT%20DECLARATION.pdf
http://eprints.uthm.edu.my/820/3/MOHD%20YUSSNI%20HASHIM%20WATERMARK.pdf
http://eprints.uthm.edu.my/820/
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Institution: Universiti Tun Hussein Onn Malaysia
Language: English
English
English
Description
Summary:This study was conducted to evaluate the alkali treatment conditions optimization impact on kenaf fiber and its short random oriented kenaf fiber reinforced polyester matrix composite mechanical properties characterization. The selected treatment conditions are alkali solution concentration (2% w/v ~ 10% w/v), immersion duration (30 minute ~ 480 minute) and immersion temperature (room temperature ~ 100oC). Two types of experimental design approach were used in this work. It was three factors at three levels full factorial design for evaluating the kenaf fiber mechanical properties characterization and Response Surface Methodology (RSM) for determining the optimum alkali treatment conditions on kenaf polyester composite mechanical properties characterization. As the outcome of this study, the significant main-and-interaction effect of alkali treatment condition for kenaf fiber was determined. Furthermore, the correlation between optimum alkali treatment conditions with enhancement of kenaf fiber polyester matrix mechanical properties was suggested in the form of regression model. Based on the results, several regression models have been constructed according to Analysis of Variance and the regression model. Confirmation tests have been conducted towards selected predicted regression model. The confirmation test results shows good agreement with the proposed regression model. Finally, the outcome with a reliable database for optimum alkali treatment condition setting presented through this dissertation is expected to enhance insight regarding the knowledge of significant parameters in alkali treatment optimization that is extensively used in natural fiber surface treatment.