Machine learning-based adjustments in volume diagnosis procedures for determination of root cause distributions
US12001973B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 22, 2019 |
| Grant date | Jun 4, 2024 |
| Priority date | — |
| Expiry date | Jul 30, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F30/333
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A computing system may include a model training engine configured to train a supervised learning model with a training set comprising training probability distributions computed for training dies through a local phase of a volume diagnosis procedure. The computing system may also include a volume diagnosis adjustment engine configured to access a diagnosis report for a given circuit die that has failed scan testing and compute, through the local phase of the volume diagnosis procedure, a probability distribution for the given circuit die from the diagnosis report. The volume diagnosis adjustment engine may also adjust the probability distribution into an adjusted probability distribution using the supervised learning model and provide the adjusted probability distribution for the given circuit die as an input to a global phase of the volume diagnosis procedure to determine a global root cause distribution for multiple circuit dies that have failed the scan testing.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.