Cited by 72Additive Manufacturing and 3D Printing TechnologiesAdditive Manufacturing Materials and ProcessesManufacturing Process and Optimization

Reverse engineering of additive manufactured composite part by toolpath reconstruction using imaging and machine learning

Open access
Yanamandra, Kaushik, Chen, Guan Lin, Xu, Xianbo, Mac, Gary, Gupta, Nikhil·2020·Composites Science and Technology

Abstract

Abstract Development of composite material parts requires significant research and development effort. The fiber size, volume fraction and direction are important in determining the properties of the part. Additive manufacturing (AM) methods are increasingly used for printing composite materials. Advancements in 3D scanning and imaging technology have raised a significant concern in reverse engineering of parts made by AM, which may result in counterfeiting and unauthorized production of high quality parts. This work is focused on using imaging methods and machine learning to reverse engineer a composite material part, where not only the geometry is captured but also the tool path of 3D printing is reconstructed using machine learning of microstructure. A dimensional accuracy with only 0.33% difference is achieved for the reverse engineered model.

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Crossref · 10.1016/j.compscitech.2020.108318

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43 of 43 references verified0 citation errors · 0 not checkable

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  • For printing composite materials, factors such as fiber size, volume fraction, and direction must be optimized to secure the desired properties for the printed part.

    “For printing composite materials, factors such as fiber size, volume fraction, and direction must be optimized to secure the desired properties for the printed part [427].”

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Authors
Yanamandra, K., Chen, G. L., Xu, X., Mac, G., & Gupta, N.
Affiliations
New York University (US)
Venue
Composites Science and Technology
Publisher
Elsevier BV
Published
2020-09
Volume
198
Pages
108318
ISSN
0266-3538 (ISSN-L)
OpenAlex
W3037035195
Cited by
72
References
43
Citations by year
2026: 10 · 2025: 10 · 2024: 11 · 2023: 16 · 2022: 13 · 2021: 9 · 2020: 3
FWCI
3.79
Type
journal article
Language
en
Open access
Locations
Composites Science and Technology (acceptedVersion)
Funders
National Science Foundation
Topics
  • Physical Sciences › Engineering › Automotive Engineering › Additive Manufacturing and 3D Printing Technologies
  • Physical Sciences › Engineering › Mechanical Engineering › Additive Manufacturing Materials and Processes
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Manufacturing Process and Optimization
Keywords
reverse engineering, additive manufacturing, composite components, 3D printing, 3D scanning, imaging, machine learning, microstructure, fiber orientation, counterfeit parts, dimensional accuracy

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