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:
Jun. 22, 2021
Filed:
Jul. 09, 2020
Applicant:
Svxr, Inc., San Jose, CA (US);
Inventors:
David Lewis Adler, San Jose, CA (US);
Freddie Erich Babian, Palo Alto, CA (US);
Scott Joseph Jewler, San Jose, CA (US);
Assignee:
SVXR, Inc., San Jose, CA (US);
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 30/398 (2020.01); G06T 7/00 (2017.01); G06N 20/00 (2019.01); G06T 5/00 (2006.01); G01N 23/04 (2018.01); G01T 1/20 (2006.01); H05K 1/11 (2006.01); H05K 3/40 (2006.01); H01L 21/67 (2006.01); G01N 23/083 (2018.01); G01N 23/18 (2018.01); G06K 9/62 (2006.01); G06F 119/18 (2020.01); G06F 115/12 (2020.01);
U.S. Cl.
CPC ...
G06T 7/0014 (2013.01); G01N 23/04 (2013.01); G01N 23/043 (2013.01); G01N 23/083 (2013.01); G01N 23/18 (2013.01); G01T 1/20 (2013.01); G06F 30/398 (2020.01); G06K 9/6256 (2013.01); G06K 9/6267 (2013.01); G06N 20/00 (2019.01); G06T 5/007 (2013.01); G06T 7/0012 (2013.01); H01L 21/67288 (2013.01); H05K 1/115 (2013.01); H05K 3/4038 (2013.01); G01N 2223/04 (2013.01); G01N 2223/401 (2013.01); G01N 2223/426 (2013.01); G01N 2223/505 (2013.01); G01N 2223/6466 (2013.01); G06F 2115/12 (2020.01); G06F 2119/18 (2020.01); G06T 2207/10081 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/20024 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20208 (2013.01); G06T 2207/30004 (2013.01);
Abstract
In one embodiment, a computing system may access design data of a printed circuit board to be produced by a first manufacturing process. The system may analyze the design data of the printed circuit board using a machine-learning model, wherein the machine-learning model is trained based on X-ray inspection data associated with the first manufacturing process. The system may automatically determine one or more corrections for the design data of the printed circuit board based on the analysis result by the machine-learning model.