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:
Aug. 22, 2023

Filed:

May. 18, 2021
Applicant:

Tata Consultancy Services Limited, Mumbai, IN;

Inventors:

Deepak Jain, Pune, IN;

Sapankumar Hiteshchandra Shah, Pune, IN;

Beena Rai, Pune, IN;

Pritwish Mitra, Pune, IN;

Sreedhar Reddy, Pune, IN;

Neelanshi Wadhwa, Pune, IN;

Sarath Sasidharan, Pune, IN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 5/022 (2023.01); G06F 16/93 (2019.01); G06F 16/901 (2019.01); G06F 40/289 (2020.01); G06N 3/08 (2023.01); G06F 40/258 (2020.01); G06F 40/295 (2020.01); G06F 40/30 (2020.01); G06F 40/279 (2020.01);
U.S. Cl.
CPC ...
G06N 5/022 (2013.01); G06F 16/9024 (2019.01); G06F 16/93 (2019.01); G06F 40/258 (2020.01); G06F 40/279 (2020.01); G06F 40/289 (2020.01); G06F 40/295 (2020.01); G06F 40/30 (2020.01); G06N 3/08 (2013.01);
Abstract

This disclosure relates generally to methods and systems for building an intelligent analytical platform to enable a device fabrication in material science. Material engineers and design engineers may face various challenges with existing knowledge, as more time and efforts are required in finding a relevant knowledge from the existing knowledge, mainly due to the unstructured form, for fabricating new devices. The present disclosure solves the technical problem of finding the relevant knowledge out of the existing knowledge, in a structured form by building an analytical platform. The unstructured format of the existing knowledge of the fabrication process is transformed into a structured format in terms of operation sequence knowledge graphs, using a set of artificial intelligence (AI) and machine learning models, and a knowledge representation model of the fabrication process. The structured format of the existing knowledge is hierarchically arranged to build the analytical platform.


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