About this Abstract |
Meeting |
2022 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2022)
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Symposium
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2022 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2022)
|
Presentation Title |
Autonomous Error Detection and Correction Powered by Deep Neural Networks |
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 human operators can detect errors but cannot provide continuous monitoring or real-time correction. This has led to much 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 describe our recent work on addressing these limitations through a novel combination of in situ imaging and deep neural networks. This enables closed-loop feedback through real-time error detection and autonomous correction to aid in the extrusion-based manufacture of end-use parts in demanding applications. |
Proceedings Inclusion? |
Definite: Post-meeting proceedings |