TY  - CONF
A1  - Altenburg, Simon
T1  - Machine Learning and Thermography as Tools for Local Porosity Prediction in AM of Metals
N2  - Quality assurance of metal additive manufacturing (PBF-LB/M) is still a challenge. Offering deep process insights, thermography is a well-suited monitoring technique. Here, we show how machine learning based on thermographic data enables a local part porosity prediction.
T2  - Laser Applications Conference (LAC)
CY  - Prague, Czech Republic
DA  - 19.10.2025
KW  - PBF-LB/M
KW  - In situ monitoring
KW  - Thermography
KW  - Additive Manufacturing
KW  - Process monitoring
KW  - Porosity prediction
KW  - Machine Learning
KW  - Feature extraction
PY  - 2025
AN  - OPUS4-64669
LA  - eng
AD  - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany
ER  -