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Accelerating process development for 3D printing of new metal alloys

Author

Listed:
  • David Guirguis

    (Carnegie Mellon University
    Carnegie Mellon University)

  • Conrad Tucker

    (Carnegie Mellon University
    Carnegie Mellon University
    Carnegie Mellon University)

  • Jack Beuth

    (Carnegie Mellon University
    Carnegie Mellon University)

Abstract

Addressing the uncertainty and variability in the quality of 3D printed metals can further the wide spread use of this technology. Process mapping for new alloys is crucial for determining optimal process parameters that consistently produce acceptable printing quality. Process mapping is typically performed by conventional methods and is used for the design of experiments and ex situ characterization of printed parts. On the other hand, in situ approaches are limited because their observable features are limited and they require complex high-cost setups to obtain temperature measurements to boost accuracy. Our method relaxes these limitations by incorporating the temporal features of molten metal dynamics during laser-metal interactions using video vision transformers and high-speed imaging. Our approach can be used in existing commercial machines and can provide in situ process maps for efficient defect and variability quantification. The generalizability of the approach is demonstrated by performing cross-dataset evaluations on alloys with different compositions and intrinsic thermofluid properties.

Suggested Citation

  • David Guirguis & Conrad Tucker & Jack Beuth, 2024. "Accelerating process development for 3D printing of new metal alloys," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-44783-5
    DOI: 10.1038/s41467-024-44783-5
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    References listed on IDEAS

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    1. Aniruddha Gaikwad & Reza Yavari & Mohammad Montazeri & Kevin Cole & Linkan Bian & Prahalada Rao, 2020. "Toward the digital twin of additive manufacturing: Integrating thermal simulations, sensing, and analytics to detect process faults," IISE Transactions, Taylor & Francis Journals, vol. 52(11), pages 1204-1217, November.
    2. Yuze Huang & Tristan G. Fleming & Samuel J. Clark & Sebastian Marussi & Kamel Fezzaa & Jeyan Thiyagalingam & Chu Lun Alex Leung & Peter D. Lee, 2022. "Keyhole fluctuation and pore formation mechanisms during laser powder bed fusion additive manufacturing," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    3. Banning Garrett, 2014. "3D Printing: New Economic Paradigms and Strategic Shifts," Global Policy, London School of Economics and Political Science, vol. 5(1), pages 70-75, February.
    4. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    5. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
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