Device for predicting aluminum product properties, method for predicting aluminum product properties, control program, and storage medium
US-2020024712-A1 · Jan 23, 2020 · US
US12083568B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-12083568-B2 |
| Application number | US-201917423476-A |
| Country | US |
| Kind code | B2 |
| Filing date | Feb 19, 2019 |
| Priority date | Jan 17, 2019 |
| Publication date | Sep 10, 2024 |
| Grant date | Sep 10, 2024 |
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A production specification determination method, a production method, and a production specification determination apparatus that can increase robustness against disturbances during production of a metal material are provided. Included are the steps of acquiring at least one piece of performance data established after a predetermined process during production of a metal material, performing back analysis based on the at least one piece of performance data and a prediction model that relates production specifications and material characteristics, and searching for production specifications for after the predetermined process such that an estimated value for the material characteristics asymptotically approaches a desired value.
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The invention claimed is: 1. A production specification determination method for a metal material, the production specification determination method comprising: acquiring, as a portion of production specifications, at least one piece of performance data established after a predetermined process during production of a metal material; and performing back analysis based on the at least one piece of performance data and a prediction model that relates the production specifications including the at least one piece of performance data and material characteristics, and optimizing, during production, production specifications for after the predetermined process by performing feedforward calculation of control amount of a process after the predetermined process in an entire production process and transmitting the control amount to the process as an instruction value such that an estimated value for the material characteristics approaches a desired value. 2. The production specification determination method of claim 1 , wherein the predetermined process is a process for adjusting a chemical composition of the metal material, and the at least one piece of performance data comprises performance data on chemical composition adjustment. 3. The production specification determination method of claim 1 , wherein the metal material is a steel plate. 4. The production specification determination method of claim 1 , wherein the material characteristics comprise uniform elongation. 5. The production specification determination method of claim 1 , wherein the prediction model is a machine learning model including a deep learning model or a statistical learning model, trained based on the production specifications and performance data of the material characteristics. 6. A production method for producing a metal material to production specifications determined using the production specification determination method of claim 1 . 7. A production specification determination apparatus comprising: a communication interface configured to acquire, as a portion of production specifications, at least one piece of performance data established after a predetermined process during production of a metal material; and a search processor configured to perform back analysis based on the at least one piece of performance data and a prediction model that relates the production specifications including the at least one piece of performance data and material characteristics, and optimize, during production, production specifications for after the predetermined process by performing feedforward calculation of control amount of a process after the predetermined process in an entire production process and transmitting the control amount to the process as an instruction value such that an estimated value for the material characteristics approaches a desired value.
characterised by using design data to control NC machines, e.g. CAD/CAM (G05B19/4093 takes precedence) · CPC title
using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model · CPC title
Geometric CAD · CPC title
Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] · CPC title
Making ferrous alloys · CPC title
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