A Random Forest Classifier for Anomaly Detection in Laser-Powder Bed Fusion Using Optical Monitoring

A Random Forest Classifier for Anomaly Detection in Laser-Powder Bed Fusion Using Optical Monitoring

Metal additive manufacturing (AM) is a disruptive production technology, widely adopted in innovative industries that revolutionizes design and manufacturing. The interest in quality control of AM systems has grown substantially over the last decade, driven by AM’s appeal for intricate, high-value,...

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Bibliographic Details
Main Authors: Imran Ali Khan, Hannes Birkhofer, Dominik Kunz, Drzewietzki Lukas, Vasily Ploshikhin
Format: Article
Language:English
Published: MDPI AG 2023-09-01
Series:Materials
Subjects:
machine learning
random forest
quality inspection
laser powder bed fusion
process monitoring
optical tomography
Online Access:https://www.mdpi.com/1996-1944/16/19/6470

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https://www.mdpi.com/1996-1944/16/19/6470

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