| About this Abstract |
| Meeting |
2023 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2023)
|
| Symposium
|
2023 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2023)
|
| Presentation Title |
End-to-end AI Models for Error Detection and Correction in Extrusion AM |
| Author(s) |
Douglas A J Brion, Sebastian W Pattinson |
| On-Site Speaker (Planned) |
Douglas A J Brion |
| Abstract Scope |
Material extrusion is the most widely used additive manufacturing method, but its use in many applications is limited by its vulnerability to diverse errors. Expert operators can detect errors but cannot provide continuous monitoring or real-time correction. This has led to significant research into automated methods for error detection. However, current approaches can often only detect limited error modalities across a narrow range of parts and materials. Additionally, errors remain particularly challenging to correct, primarily requiring manual intervention. This talk will discuss the application of recent advances in large AI models and deep learning to tackle these problems. End-to-end models show great promise for detecting errors autonomously and powering feedback systems that can correct process parameters in real time, opening the door to improved part quality and uptake in end-use applications. |
| Proceedings Inclusion? |
Definite: Post-meeting proceedings |