Application of micro-computed tomography for authentication of 3D printed composite parts

•Tomography analysis is used to study 3D printed fiber-reinforced composite parts.•The samples are different in infill printing direction and the presence of an outer wall.•Part identification methods are developed based on fibers, porosity, and printing features.•Frequency domain analysis captures...

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Veröffentlicht in:Additive manufacturing letters 2022-12, Vol.3, p.100104, Article 100104
Hauptverfasser: Mac, Gary, Mandal, Meenakshi, Rastogi, Aryan, Gailani, Gaffar, Pearce, Hammond, Gupta, Nikhil
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Sprache:eng
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Zusammenfassung:•Tomography analysis is used to study 3D printed fiber-reinforced composite parts.•The samples are different in infill printing direction and the presence of an outer wall.•Part identification methods are developed based on fibers, porosity, and printing features.•Frequency domain analysis captures distinguishing differences in CT datasets.•The result can be used for part authentication procedures for AM composite parts. Additive Manufacturing (AM) can apply unique customized printing patterns for each layer, which govern the microstructural features in a fiber-reinforced composite part. Non-destructive evaluation methods are used extensively to understand the defects and the microstructure of 3D printed composite parts. Considerable intellectual property is involved in designing and manufacturing composite parts, which needs to be protected using innovative methods. One of the concerns in this area is counterfeit parts made on high quality 3D printers, which need to be identified. This study aims to investigate and provide a part-authentication methodology for 3D printed composite parts by using the micro-computed tomography (μCT) scans of discontinuous fiber-reinforced polymer composite (FRPC) parts. The microstructure of FRPC contains fibers, matrix and porosity that are unique to the specimen and is a result of the printing parameters. Specimen A is printed with an infill direction of 90∘ and wall count of 3 and specimen B has the same infill direction but does not contain a wall boundary. A comparison between the different μCT datasets of the specimens can identify the distinguishing features of the 3D printed composite part. The correlation developed across different μCT datasets from extracted features and the metrics formulated can be used to quantitatively differentiate the composite specimens. Frequency domain analysis shows the most promising results by correctly identifying 3 out of the 6 datasets belonging to the same AM. A part identification and authentication method for AM composites will be useful for identifying genuine or counterfeit parts and protect intellectual property.
ISSN:2772-3690
2772-3690
DOI:10.1016/j.addlet.2022.100104