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.

Date of Patent:
Jun. 10, 2025

Filed:

Feb. 21, 2022
Applicant:

The Johns Hopkins University, Baltimore, MD (US);

Inventors:

Steven M. Storck, Catonsville, MD (US);

Nathan G. Drenkow, Columbia, MD (US);

Brendan P. Croom, Baltimore, MD (US);

Ryan H. Carter, Ellicott City, MD (US);

Robert K. Mueller, Columbia, MD (US);

Assignee:

The Johns Hopkins University, Baltimore, MD (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
B33Y 50/02 (2015.01); B29C 64/153 (2017.01); B29C 64/393 (2017.01); B33Y 10/00 (2015.01); G06T 7/00 (2017.01); G06V 10/70 (2022.01);
U.S. Cl.
CPC ...
B29C 64/393 (2017.08); B29C 64/153 (2017.08); B33Y 10/00 (2014.12); B33Y 50/02 (2014.12); G06T 7/0004 (2013.01); G06V 10/70 (2022.01); B29C 2791/009 (2013.01); G06T 2207/10048 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30144 (2013.01);
Abstract

A method for monitoring and analyzing an additive manufacturing process includes heating a melt zone to fuse an additive media with an active layer to build a part being manufactured based on a part design model, capturing raw melt data of the melt zone, and generating an active layer dataset that is spatially defined. The method may also include analyzing the active layer dataset with respect to a plurality of defect signatures within a defect signature library. The defect signature library may be predefined based on a machine learning processing of historical sensor datasets with corresponding ground truth datasets. The method may also include detecting a defect in the part based on the analysis of the active layer dataset with respect to a plurality of defect signatures, simultaneously with the energy source acting upon the active layer of the part for manufacturing of the part.


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