Machine learning approach for fatigue life prediction of additive manufactured components accounting for localized material properties
US11586161B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Jul 10, 2019 |
| Grant date | Feb 21, 2023 |
| Priority date | — |
| Expiry date | Jul 10, 2039 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02P10/25
- WIPO fieldControl
- WIPO sectorInstruments
Abstract
A method and a system for fatigue life prediction of additive manufactured components accounting for localized material properties. The method and the system is employed for prediction of fatigue life properties of an additive manufactured element, with a data collection step in which several data points for maximum stress vs. cycles to failure for different given processing steps of the element are collected, with a training step in which a Machine Learning system is trained with the collected data, and with an evaluation step in which the trained Machine Learning system is confronted with actual processing steps and used to predict the fatigue life properties of the element.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.