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- 저자 : Mastura M. T. (검색결과 2 건)
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Mastura M. T.,Sapuan S. M.,Mansor M. R.,Nuraini A. A. 한국정밀공학회 2018 International Journal of Precision Engineering and Vol.5 No.1
In this study, selection of thermoplastic polymers to be used in natural fibre-reinforced polymer composite is performed using Quality Function Deployment for Environment technique. The candidate materials for the matrix in composites are thermoplastic polyurethane, high-density polyethylene, low-density polyethylene, polystyrene and polypropylene and the selection process is carried out based on the design requirements of an automotive anti-roll bar. Requirements are collected through a study on the voice of customers and the voice of the environment. The approach is followed by sensitivity analysis using Expert Choice software based on the Analytic Hierarchy Process method. From the analysis, high-density polyethylene scored the highest (28.76%), and followed by thermoplastic polyurethane, which had 22.30%of the overall score. Finally, Young’s modulus of hemp fibre reinforced high-density polyethylene and thermoplastic polyurethane composites were compared, predicted using the Halpin-Tsai method. The results show that hemp-reinforced thermoplastic polyurethane composite shows higher Young’s modulus of 10.6 GPa, compared with hemp-reinforced high-density polyethylene composite (8.27 GPa). Based on these two analyses, thermoplastic polyurethane is selected as the most suitable polymer matrix for natural fibre composites for automotive anti-roll bar.
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M. Noryani,S.M. Sapuan,M. T. Mastura,M. Y. M. Zuhri,E. S. Zainudin 한국섬유공학회 2018 Fibers and polymers Vol.19 No.5
Material selection is an important stage in the development of products from composites process of automotive component application. Numerious different Multi-Criteria Decision-Making tools have their own strenghts and limitations. This paper presents a framework for material selection of natural fibre reinforced polymer composites by using statistical approach. The framework is developed using statistical methods which are simple, multiple and stepwise regression for the material selection process. The performance of potential material is investigated by a statistical analysis such as coefficient of correlation, coefficient of determination and analysis of variance. A case study to select the best composite of parking brake lever is applied to this framework. End results revealed that kenaf reinforced polypropylene is the best candidate for construction of automotive parking brake lever component. The best possible of statistical model for material selection of the composite can be referred by design engineer in composite industry for a multiple application. Moreover, the proposed framework is an aid to help engineers and designers to choose most suitable material.
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