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Prediction of surface profile in CFRP machining through phenomenological analysis and inverse continuous wavelet transformation
Citation Link: https://doi.org/10.15480/882.13120
Publikationstyp
Conference Paper
Date Issued
2024-06
Sprache
English
TORE-DOI
Journal
Volume
123
Start Page
143
End Page
148
Article Number
Elsevier
Citation
7th CIRP Conference on Surface Integrity, CSI 2024
Contribution to Conference
Publisher DOI
Scopus ID
Carbon fibre-reinforced polymer (CFRP) is favored for its high strength to weight ratio, outstanding direction dependent mechanical properties and the high potential for load adapted design. However, machining unidirectional CFRP is challenging due to its anisotropic behavior, resulting in variable surface quality under identical machining parameters with different fibre orientations. Recently, a universal, process-independent model describing the engagement conditions in oblique cutting of unidirectional CFRPs has been developed, introducing the spatial fibre cutting angle θ0 and the spatial engagement angle ϕ0. Milling and drilling are mostly used for machining CFRP. Since the engagement conditions are rather complex, first analogy experiments are conducted in turning with variation of the setting and inclination angles. In this study, continuous surface profiles were recorded as a function of the spatial fibre cutting angle. Phenomenological and continuous wavelet analyses can be used to describe the surface profiles as a function of the spatial engagement conditions and to accurately predict them and the surface roughness using an inverse wavelet transformation. Experimental investigations with a side milling process of CFRP validate the prediction approach and show a good agreement between the experimental and predicted surface profiles.
Subjects
carbon fibre reinforced plastics
carbon fibre reinforced polymers, cutting
sawing
spatial engagement conditions
surface roughness
turning
DDC Class
620.1: Engineering Mechanics and Materials Science
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1-s2.0-S2212827124002312-main.pdf
Type
Main Article
Size
2.04 MB
Format
Adobe PDF