Improving Build Quality in Laser Powder Bed Fusion Using High Dynamic Range Imaging and Model-Based Reinforcement Learning

Improving Build Quality in Laser Powder Bed Fusion Using High Dynamic Range Imaging and Model-Based Reinforcement Learning

In laser-based additive manufacturing (AM) of metal parts from powder bed, information about actual part quality obtained during build is essential for cost-efficient production and high product quality. Reliable and effective monitoring strategies for laser powder bed fusion (LPBF) therefore remain...

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Bibliographic Details
Main Authors: Christian Knaak, Lukas Masseling, Emil Duong, Peter Abels, Arnold Gillner
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Laser powder bed fusion
convolutional neural networks
model-based reinforcement learning
high dynamic range imaging
surface roughness optimization
Online Access:https://ieeexplore.ieee.org/document/9381862/

Internet

https://ieeexplore.ieee.org/document/9381862/

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