The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Aug. 12, 2025
Filed:
Jul. 29, 2021
The Penn State Research Foundation, University Park, PA (US);
Edward Reutzel, University Park, PA (US);
Jan Petrich, University Park, PA (US);
Abdalla R. Nassar, University Park, PA (US);
Shashi Phoha, University Park, PA (US);
David J. Corbin, University Park, PA (US);
Jacob P. Morgan, University Park, PA (US);
Evan P. Diewald, University Park, PA (US);
Robert W. Smith, University Park, PA (US);
Zackary Keller Snow, University Park, PA (US);
THE PENN STATE RESEARCH FOUNDATION, University Park, PA (US);
Abstract
Embodiments relate to in-situ process monitoring of a part being made via additive manufacturing. The process can involve capturing computed tomography (CT) scans of a post-built part. A neural network (NN) can be used during the build of a new part to process multi-modal sensor data. Spatial and temporal registration techniques can be used to align the data to x,y,z coordinates on the build plate. During the build of the part, the multi-modal sensor data can be superimposed on the build plate. Machine learning can be used to train the NN to correlate the sensor data to a defect label or a non-defect label by looking to certain patterns in the sensor data at the x,y,z location to identify a defect in the CT scan at x,y,z. The NN can then be used to predict where defects are or will occur during an actual build of a part.