Powder Bed Monitoring Using Semantic Image Segmentation to Detect Failures during 3D Metal Printing

Powder Bed Monitoring Using Semantic Image Segmentation to Detect Failures during 3D Metal Printing

Monitoring the metal Additive Manufacturing (AM) process is an important task within the scope of quality assurance. This article presents a method to gain insights into process quality by comparing the actual and target layers. Images of the powder bed were captured and segmented using an Xception–...

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Bibliographic Details
Main Authors: Höfflin, D. (Author), Sauer, C. (Author), Schiffler, A. (Author), Schmitt, A.-M (Author)
Format: Article
Language:English
Published: MDPI 2023
Subjects:
3d metals
3D printing
additive manufacturing
Additive manufacturing process
Additives
in situ monitoring
In-situ monitoring
Metal additives
metal printing
Metal printings
neural network
Neural-networks
Powder bed
Powder metals
Quality assurance
Semantic image segmentations
semantic segmentation
Semantic segmentation
Semantic Segmentation
Semantic Web
Semantics
thermal distortion
Thermal distortions
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