| About this Abstract |
| Meeting |
2024 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2024)
|
| Symposium
|
2024 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2024)
|
| Presentation Title |
Multimodal Federated Product-of-Experts for Collaborative Fatigue Life Prediction in Additive Manufacturing |
| Author(s) |
Anyi Li, Jia Liu |
| On-Site Speaker (Planned) |
Anyi Li |
| Abstract Scope |
Accurately predicting the fatigue life of additive manufactured (AM) parts from inspection and testing data is crucial for their adoption in critical applications like aerospace. However, not every manufacturer possesses nondestructive inspection or fatigue testing capability to enable their efforts in fatigue life prediction. Also, inspection and testing specimens are too limited to build an accurate predictive model for individual manufacturers. To tackle these challenges, we propose a multimodal federated product-of-experts (MMFedPoE) framework, which can aggregate information from the manufacturers for collaborative fatigue life prediction without sharing their proprietary data. Manufacturers can train fatigue life prediction models based on their fabrication conditions and inspection or testing capabilities (e.g., X-ray CT scans, fatigue testing conditions). Then MMFedPoE trains joint distributions of different inspection and testing data by employing a product-of-experts approach and shares their distributions among the manufacturers. MMFedPoE can benefit manufacturers with different capabilities in accurate fatigue life prediction. |
| Proceedings Inclusion? |
Definite: Post-meeting proceedings |