Measurement of laser-based powder bed fusion (PBF-LB) surfaces provides a promising solution for closed-loop quality control of the final parts. This paper presents a light scattering method to measure PBF-LB surfaces combined with oneclass support vector machines (SVMs) for anomaly (defect) detection during the manufacturing process. With the oneclass SVM method, datasets from solely reference (acceptable) surfaces are used to fit a classification model. Experimental results show that the method is fast and has higher accuracy than our previous work, which is promising for integration into next-generation PBF-LB machines for process quality monitoring.
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