Threshold determination for predictive process control of factory processes, equipment and automated systems
US12153387B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 31, 2023 |
| Grant date | Nov 26, 2024 |
| Priority date | — |
| Expiry date | Aug 31, 2043 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02P90/02
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
A deep learning process receives desired process values associated with the one or more process stations. The deep learning processor receives desired target values for one or more key performance indicators of the manufacturing process. The deep learning processor simulates the manufacturing process to generate expected process values and expected target values for the one or more key performance indicators to optimize the one or more key performance indicators. The simulating includes generating a proposed state change of at least one processing parameter of the initial set of processing parameters. The deep learning processor determines that expected process values and the expected target values are within an acceptable limit of the desired process values and the desired target values. Based on the determining, the deep learning processes causes a change to the initial set of processing parameters based on the proposed state change.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.