Systems and methods for part tracking using machine learning techniques
US12246399B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Apr 23, 2021 |
| Grant date | Mar 11, 2025 |
| Priority date | — |
| Expiry date | Jul 22, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for part tracking using machine learning techniques are described. In some examples a part tracking system analyzes feature characteristics related to one or more welds to identify, determine characteristics of, and/or label one or more parts repeatedly assembled by the welds. Identifying parts assembled from the welds may make it possible to do part based analytics (e.g., related to part quality, cost, production efficiency, etc.), as opposed to just weld based analytics, on past welding data. Additionally, identifying a part assembled from several welds results in an ordering of those several welds used to create the part, which can make it easier to compare/contrast similar welds across parts. Further, determining the characteristics of the parts can assist in configuring certain part tracking systems, thereby reducing the expertise, time, and personnel required.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.