Identification of hot spots or defects by machine learning
US11443083B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Apr 20, 2017 |
| Grant date | Sep 13, 2022 |
| Priority date | — |
| Expiry date | Sep 28, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V2201/06
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods of identifying a hot spot from a design layout or of predicting whether a pattern in a design layout is defective, using a machine learning model. An example method disclosed herein includes obtaining sets of one or more characteristics of performance of hot spots, respectively, under a plurality of process conditions, respectively, in a device manufacturing process; determining, for each of the process conditions, for each of the hot spots, based on the one or more characteristics under that process condition, whether that hot spot is defective; obtaining a characteristic of each of the process conditions; obtaining a characteristic of each of the hot spots; and training a machine learning model using a training set including the characteristic of one of the process conditions, the characteristic of one of the hot spots, and whether that hot spot is defective under that process condition.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.