Cited by 15Additive Manufacturing Materials and ProcessesAdditive Manufacturing and 3D Printing TechnologiesWelding Techniques and Residual Stresses

Laser scan strategy descriptor for defect prognosis in metal additive manufacturing using neural networks

Open access
Demir, Kahraman, Zhang, Zhizhou, Ben-Artzy, Adi, Hosemann, Peter, Gu, Grace X.·2021·Journal of Manufacturing Processes

Integrity signals

Registry

Crossref · 10.1016/j.jmapro.2021.05.011

Cites

33 of 33 references verified0 citation errors · 0 not checkable

Statistics

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  • Machine learning models can be developed to predict mechanical properties of materials fabricated through additive manufacturing as they can learn and model highly complex relationships.

    “Machine learning models can be developed to predict mechanical properties of materials fabricated through additive manufacturing as they can learn and model highly complex relationships [438-445].”

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Authors
Demir, K., Zhang, Z., Ben-Artzy, A., Hosemann, P., & Gu, G. X.
Affiliations
  • University of California, Berkeley (US)
  • Ben-Gurion University of the Negev (IL)
Corresponding author
Gu, Grace X.
Venue
Journal of Manufacturing Processes
Publisher
Elsevier BV
Published
2021-07
Volume
67
Pages
628-634
ISSN
1526-6125 (ISSN-L)
OpenAlex
W3160488492
Cited by
15
References
33
Citations by year
2026: 1 · 2025: 4 · 2024: 5 · 2023: 2 · 2022: 2 · 2021: 1
FWCI
1.05
Type
journal article
Language
en
Open access
Locations
Journal of Manufacturing Processes (acceptedVersion)
Funders
  • University of California Berkeley
  • National Science Foundation
  • National Science Foundation Directorate for Engineering (ACI-1548562)
  • 3M
Topics
  • Physical Sciences › Engineering › Mechanical Engineering › Additive Manufacturing Materials and Processes
  • Physical Sciences › Engineering › Automotive Engineering › Additive Manufacturing and 3D Printing Technologies
  • Physical Sciences › Engineering › Mechanical Engineering › Welding Techniques and Residual Stresses
Keywords
metal additive manufacturing, powder bed fusion, residual stress prediction, microstructural properties, neural network prediction, in situ monitoring

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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