United States
US 12,697,781 B1
Machine learning for real-time monitoring and control of additive manufacturing
US 12,697,781 B1 is a granted patent from the United States Patent and Trademark Office (USPTO), dated 2026-08-04. Applicant: National Technology & Engineering Solutions of Sandia, LLC. Its PDF downloads from this page without an account, up to 5 a day.
- Applicant
- National Technology & Engineering Solutions of Sandia, LLC
- Inventors
- Devin John Roach; Andrew Rohskopf; William Derek Reinholtz; Adam Wade Cook; Leah N. Appelhans
- Publication date
- 2026-08-04
- Filing date
- 2023-10-10
- Document type
- B1 Granted patent
- Also written as
- US 12,697,781 B1 · US12697781 · 12697781
Abstract
A machine learning (ML) approach enables real-time direct ink write (DIW) print-parameter optimization through in-situ monitoring of printed line geometry. The method can use an invertible neural network (INN) to solve both forward and inverse, or optimization, problems using a single network. By combining in-situ computer vision and INNs, DIW printing parameters can be autonomously optimized to print a target line width in a matter of seconds. Furthermore, defects that occur during printing can be rapidly identified and corrected autonomously.…
The opening of the abstract. The full text is in the PDF.
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Patent office website: United States Patent and Trademark Office (USPTO)
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