Systems and methods for identifying missing welds using machine learning techniques
US12251773B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | May 13, 2021 |
| Grant date | Mar 18, 2025 |
| Priority date | — |
| Expiry date | Oct 13, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30164
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for missing weld identification using machine learning techniques are described. In some examples, a part tracking system uses machine learning techniques to identify whether an operator has missed one or more welds when assembling a part. The part tracking system may additionally identify which specific welds were missed (e.g., the first weld, the third weld, the fifteenth weld, etc.). The part tracking system may be able to identify missing welds after a part has been completed, or in real-time, during assembly of the part. Identification of the particular weld(s) missed during the welding process can help an operator quickly assess and resolve any issues with the part being assembled, saving time and ensuring quality.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.