Surfel convolutional neural network for support detection in additive manufacturing
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A machine learning model can be developed that enables designs for which a minimum amount of support is required.
“A machine learning model can be developed that enables designs for which a minimum amount of support is required [426].”
From A comprehensive review of lunar-based manufacturing and construction (2024) · cites this paper as [426]
The Support learning pipeline (p. 4) proposes a deep-learning model to detect where an existing design needs support, addressing redundant supports. But Support generation (p. 3) says this work focuses on detecting support regions, and the Conclusions (p. 11) place deep-learning-based support structure generation in future work. The paper does not establish that the model enables designs requiring a minimum amount of support. (LLM, conf=0.85)
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Cited by
Sorted by citations
A comprehensive review of lunar-based manufacturing and construction
Azami, M., Kazemi, Z., Moazen, S., Dubé, M., Potvin, M.-J., & Skonieczny, K. (2024) · Progress in Aerospace Sciences · doi:10.1016/j.paerosci.2024.101045 · Cited by 57 · see citing works
- Authors
- Huang, J., Kwok, T.-H., Zhou, C., & Xu, W.
- Affiliations
- University at Buffalo, State University of New York (US)
- Concordia University (CA)
- Corresponding author
- Zhou, Chi
- Venue
- The International Journal of Advanced Manufacturing Technology
- Published
- 2019-05-06
- Volume
- 105
- Issue
- 9
- Pages
- 3593-3604
- ISSN
- 0268-3768 (ISSN-L)
- 1433-3015
- OpenAlex
- W2944050272
- Cited by
- 26
- References
- 31
- Citations by year
- 2026: 3 · 2025: 3 · 2024: 3 · 2023: 7 · 2022: 3 · 2021: 3 · 2020: 3 · 2019: 1
- FWCI
- 1.14
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The International Journal of Advanced Manufacturing Technology (publishedVersion)
- Spectrum Research Repository (Concordia University) (acceptedVersion)
- Funders
- Division of Computer and Network Systems (1547167)
- Natural Sciences and Engineering Research Council of Canada (RGPIN-2017-06707)
- Topics
- Physical Sciences › Engineering › Automotive Engineering › Additive Manufacturing and 3D Printing Technologies
- Physical Sciences › Engineering › Computational Mechanics › 3D Shape Modeling and Analysis
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Manufacturing Process and Optimization
- Keywords
- support detection, support structure generation, 3D printing, surfels, overhang structures
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