Predicting reliability of product and part combinations using machine learning based on shared model
US10599992B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 10, 2015 |
| Grant date | Mar 24, 2020 |
| Priority date | — |
| Expiry date | Jan 23, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/04
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An apparatus comprises a processing platform configured to implement a machine learning system for automated generation of predicted reliability measures and associated early warning indicators for product and part combinations. The machine learning system comprises a data aggregation module configured to extract product and part data from a big data repository, and a reliability predictor configured to generate predicted reliability measures for respective ones of the product and part combinations utilizing a shared model that is determined based at least in part on the extracted product and part data. The machine learning system processes the predicted reliability measures to generate early warning indicators relating to particular ones of the product and part combinations having predicted reliability measures that fail to meet one or more specified criteria. The machine learning system illustratively provides the early warning indicators to a visualization interface so as to facilitate user adjustment of a product line.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.