About this Abstract |
Meeting |
2021 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2021)
|
Symposium
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Process Development
|
Presentation Title |
In-situ Detection of Laser Powder Bed Fusion Process Signatures Based on Sensor Fusion Approach |
Author(s) |
Ivan Zhirnov, Dean-Paul Kouprianoff, Mikael Åsberg, Pavel Krakhmalev |
On-Site Speaker (Planned) |
Ivan Zhirnov |
Abstract Scope |
A large amount of process monitoring data can currently be produced for the laser powder bed fusion process. There are more than 50 parameters that have an impact on the build quality, which cause a large number of process signatures. The accuracy of machine learning depends on the diversity of the data rather than on the quantity. In this research, different types of sensors are used to investigate the in-situ formation of cracks and delamination. Specific digital representation of crack formation was found and compared for different materials. This paper describes a multi-sensor setup and current results relating to the process signature of single tracks and layers for different LPBF machines. The proposed approach will be used in preparation for well-characterized labelled data for machine learning quality prediction. |
Proceedings Inclusion? |
Definite: Post-meeting proceedings |