About this Abstract |
| Meeting |
2026 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2026)
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| Symposium
|
2026 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2026)
|
| Presentation Title |
Active Thermography of Laser-Powder Bed Fusion Additive Manufacturing 316 Stainless Steel |
| Author(s) |
Chase Joslin |
| On-Site Speaker (Planned) |
Chase Joslin |
| Abstract Scope |
Laser-powder bed fusion additive manufacturing (L-PBF AM) continues to be a reliable tool for creating complex geometries. However, evaluation techniques do not yet fully certify and qualify L-PBF AM components. This study used flash thermography to investigate the viability of detecting subsurface porosity ex-situ. Then, in-situ active thermography was utilized to observe changes in layer-wise thermal signatures on 316 stainless steel (SS) L-PBF AM parts. Imaging the surface of printed SS with a near-infrared camera and an on-axis photodiode identified sub-surface pores in-situ. A dynamic multiscale convolutional neural network (DMSCNN) was trained to classify 2-dimensional (2D) visible-light, near-infrared, and photodiode images. A regression model was fit to predict percent porosity using DMSCNN results. Parts printed with surrogate pores had a correlation coefficient of 0.795. Although the regression model did not accurately predict porosity within control parts, the experiment shows viability to detect large scale lack-of-fusion porosity in L-PBF AM in-situ. |
| Proceedings Inclusion? |
Planned: Post-meeting proceedings |