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:

Aug. 16, 2021
Applicant:

Jfe Steel Corporation, Tokyo, JP;

Inventors:

Mayumi Ojima, Tokyo, JP;

Yoshimasa Funakawa, Tokyo, JP;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
C21D 11/00 (2006.01); B21B 37/76 (2006.01); C21D 8/02 (2026.01); C21D 8/0247 (2026.01); C21D 8/0278 (2026.01); C21D 9/46 (2006.01); G05B 13/02 (2006.01); G05B 13/04 (2006.01);
U.S. Cl.
CPC ...
C21D 11/00 (2013.01); B21B 37/76 (2013.01); C21D 8/02 (2013.01); C21D 8/0263 (2013.01); C21D 8/0278 (2013.01); C21D 9/46 (2013.01); G05B 13/0265 (2013.01); G05B 13/048 (2013.01);
Abstract

A material characteristic value prediction system that can predict material characteristic values with high accuracy is provided. Also provided is a method of manufacturing a metal sheet that can improve the product yield rate, by changing manufacturing conditions of subsequent processes. The material characteristic value prediction system () includes a material characteristic value predictor configured to acquire input data including line output factors in a metal sheet manufacturing line, disturbance factors, and component values of a metal sheet being manufactured, and predict material characteristic values of the manufactured metal sheet using a prediction model configured to take the input data as inputs, wherein the prediction model includes a machine learning model generated by machine learning and configured to take the input data as inputs and output production condition factors, and a metallurgical model configured to take the production condition factors as inputs and output the material characteristic values.


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