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Effect of milling parameters on the surface quality of a flax fiber-reinforced polymer composite

Mohamed Slamani, Hamza Chafai, J-F. Chatelain

2022Proceedings of the Institution of Mechanical Engineers Part E Journal of Process Mechanical Engineering32 citationsDOIOpen Access PDF

Abstract

Flax fiber-reinforced polymer composites are an interesting alternative to synthetic fiber-reinforced polymer composites for many engineering applications. When machining flax fiber-reinforced composite materials that are by definition heterogeneous, the matrix and the fibers react differently and hence many sorts of damage may occur such as poor surface roughness, delamination, and fluffing. The novelty of the current work lies in identifying the major factors that affect the quality of the milled surface of composites reinforced with flax fibers and provides recommendations and collaborative solutions to the composite machining community. In this study, the impact of cutting conditions (cutting speed, feed rate, and fiber orientation) on the cutting forces and surface roughness during milling of the flax/epoxy composite is investigated. For this purpose, slotting tests are performed on flax fiber-reinforced polymer plates using a carbide end mill tool based on a full factorial design of experiment. Furthermore, a randomization in the order in which experimental runs are done is used to reduce bias by balancing the effect of uncontrolled variables that have not been accounted for in the experimental design. It is concluded that the feed rate has the most influence on the cutting forces and roughness parameters. Moreover, the fibers orientation also has a significant effect on the outputs, and the cutting speed has less effect but it remains significant.

Topics & Concepts

Materials scienceComposite materialComposite numberDelamination (geology)FiberSurface roughnessMachiningEpoxyFactorial experimentResponse surface methodologyFiber-reinforced compositeSurface finishComputer sciencePaleontologyBiologyMetallurgySubductionTectonicsMachine learningNatural Fiber Reinforced CompositesMechanical Engineering and Vibrations ResearchTribology and Wear Analysis
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