Rating substrate support assemblies based on impedance circuit electron flow using machine learning
US12205791B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jan 26, 2021 |
| Grant date | Jan 21, 2025 |
| Priority date | — |
| Expiry date | Nov 25, 2043 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04Q2209/823
- WIPO fieldElectrical machinery, apparatus, energy
- WIPO sectorElectrical engineering
Abstract
Methods and systems for rating a current substrate support assembly based on impedance circuit electron flow are provided. Data associated with an amount of radio frequency (RF) power flowed through an electrical component of a current substrate support assembly during a current testing process performed for the current substrate support assembly is provided as input to a trained machine learning model. One or more outputs of the trained machine learning model are obtained. A measurement value for an electron flow across an impedance circuit of the current substrate support assembly is extracted from the one or more outputs. In response to a determination that the extracted measurement value for the electron flow satisfies an electron flow criterion, a first quality rating is assigned to the current substrate support assembly.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.