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:
Jul. 07, 2026

Filed:

Feb. 28, 2022
Applicant:

Strong Force Vcn Portfolio 2019, Llc, Fort Lauderdale, FL (US);

Inventors:

Charles H. Cella, Pembroke, MA (US);

Brent Bliven, Austin, TX (US);

Kunal Sharma, Mumbai, IN;

Teymour S. El-Tahry, Detroit, MI (US);

Assignee:

STRONG FORCE VCN PORTFOLIO 2019, LLC, Fort Lauderdale, FL (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 20/14 (2012.01); B22F 10/85 (2021.01); B25J 9/16 (2006.01); B29C 64/357 (2017.01); B29C 64/379 (2017.01); B29C 64/386 (2017.01); B29C 64/393 (2017.01); B33Y 10/00 (2015.01); B33Y 40/00 (2020.01); B33Y 50/00 (2015.01); B33Y 50/02 (2015.01); G02B 3/14 (2006.01); G02B 26/00 (2006.01); G05B 13/02 (2006.01); G05B 13/04 (2006.01); G05B 17/02 (2006.01); G05B 19/402 (2006.01); G05B 19/4099 (2006.01); G05B 19/418 (2006.01); G05D 1/00 (2006.01); G05D 1/221 (2024.01); G05D 1/698 (2024.01); G06F 30/27 (2020.01); G06N 3/006 (2023.01); G06N 3/045 (2023.01); G06N 3/0464 (2023.01); G06N 3/084 (2023.01); G06N 3/088 (2023.01); G06N 3/09 (2023.01); G06N 5/025 (2023.01); G06N 20/00 (2019.01); G06N 20/10 (2019.01); G06N 20/20 (2019.01); G06Q 10/0631 (2023.01); G06Q 10/0633 (2023.01); G06T 7/70 (2017.01); H04L 9/00 (2022.01); H04L 9/32 (2006.01); H04L 9/40 (2022.01); B22F 10/70 (2021.01); B29C 64/10 (2017.01); G06F 113/10 (2020.01); G06Q 10/06 (2023.01); G06Q 10/0831 (2023.01); G06Q 10/0833 (2023.01); G06Q 10/087 (2023.01); G06Q 30/0201 (2023.01);
U.S. Cl.
CPC ...
G06Q 20/14 (2013.01); B22F 10/85 (2021.01); B25J 9/161 (2013.01); B25J 9/163 (2013.01); B25J 9/1653 (2013.01); B25J 9/1661 (2013.01); B25J 9/1671 (2013.01); B25J 9/1682 (2013.01); B25J 9/1697 (2013.01); B29C 64/357 (2017.08); B29C 64/379 (2017.08); B29C 64/386 (2017.08); B29C 64/393 (2017.08); B33Y 10/00 (2014.12); B33Y 40/00 (2014.12); B33Y 50/00 (2014.12); B33Y 50/02 (2014.12); G02B 3/14 (2013.01); G02B 26/00 (2013.01); G05B 13/0265 (2013.01); G05B 13/042 (2013.01); G05B 17/02 (2013.01); G05B 19/402 (2013.01); G05B 19/4099 (2013.01); G05B 19/41865 (2013.01); G05D 1/0027 (2013.01); G05D 1/0297 (2013.01); G05D 1/221 (2024.01); G05D 1/6987 (2024.01); G06F 30/27 (2020.01); G06N 3/006 (2013.01); G06N 3/045 (2023.01); G06N 3/0464 (2023.01); G06N 3/084 (2013.01); G06N 3/088 (2013.01); G06N 3/09 (2023.01); G06N 5/025 (2013.01); G06N 20/00 (2019.01); G06N 20/10 (2019.01); G06N 20/20 (2019.01); G06Q 10/06311 (2013.01); G06Q 10/0633 (2013.01); G06T 7/70 (2017.01); H04L 9/3239 (2013.01); H04L 9/50 (2022.05); H04L 63/1441 (2013.01); B22F 10/70 (2021.01); B22F 2998/00 (2013.01); B29C 64/10 (2017.08); G05B 2219/32015 (2013.01); G05B 2219/32117 (2013.01); G05B 2219/32254 (2013.01); G05B 2219/32291 (2013.01); G05B 2219/32365 (2013.01); G05B 2219/33006 (2013.01); G05B 2219/36252 (2013.01); G05B 2219/39146 (2013.01); G05B 2219/39167 (2013.01); G05B 2219/40113 (2013.01); G05B 2219/49023 (2013.01); G06F 2113/10 (2020.01); G06Q 10/06 (2013.01); G06Q 10/0631 (2013.01); G06Q 10/063114 (2013.01); G06Q 10/06313 (2013.01); G06Q 10/06316 (2013.01); G06Q 10/0831 (2013.01); G06Q 10/0833 (2013.01); G06Q 10/087 (2013.01); G06Q 30/0201 (2013.01); G06Q 2220/00 (2013.01); G06T 2207/20081 (2013.01); Y02P 90/30 (2015.11);
Abstract

An information technology system for a distributed manufacturing network includes an additive manufacturing management platform with an artificial intelligence system configured to learn on a training set of outcomes, parameters, and data collected from a set of distributed manufacturing network entities and execute simulations on digital twins of the set of distributed manufacturing network entities to make classifications, predictions, and optimization-related decisions for the set of distributed manufacturing network entities. The information technology system includes a distributed ledger system integrated with a digital thread and configured to provide unified views of workflow and transaction information to the set of distributed manufacturing network entities.


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