About this Abstract |
| Meeting |
2026 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2026)
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| Symposium
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2026 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2026)
|
| Presentation Title |
Segment-Resolved Probabilistic Defect Quantification in PBF-LB/M Single Scan Tracks Using µCT-Referenced Photodiode Features |
| Author(s) |
Jonathan Utsch, Jana Harbig, David Zentgraf, Matthias Weigold, Holger Merschroth |
| On-Site Speaker (Planned) |
Jonathan Utsch |
| Abstract Scope |
Reliable quality assessment in powder bed fusion – laser beam of metals (PBF-LB/M) requires not only defect detection but also quantitative estimation of defect occurrence and severity. This study presents an experimental validation of a probabilistic defect quantification approach based on synchronized laser scanner position data, on-axis photodiode signals and micro-computed tomography. To isolate fundamental correlations between defect formation and monitoring signal features single melt tracks generated from a systematic process parameter variation are analyzed. Due to the limited spatial-temporal resolution of monitoring signals and the stochastic nature of melt pool dynamics, defect-specific assignment is challenging, making segment-wise probabilistic estimation more robust. Therefore, scan tracks are discretized into fixed-length segments, enabling localized correlation of process signatures with µCT-based defect count and size. Process-physically motivated signal features are subsequently used as informative priors for Bayesian inference of defect probability and severity. |
| Proceedings Inclusion? |
Undecided |