In-situ defect detection in laser-directed energy deposition with machine learning and multi-sensor fusion

In-situ defect detection in laser-directed energy deposition with machine learning and multi-sensor fusion

Early defect identification in laser-directed energy deposition (L-DED) additive manufacturing (AM) is pivotal for preventing build failures. Traditional single-modal monitoring approaches lack the capability to fully comprehend process dynamics, leading to a gap in multisensor monitoring strategies...

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Bibliographic Details
Main Authors: Chen, Lequn, Moon, Seung Ki
Other Authors: School of Mechanical and Aerospace Engineering
Format: Journal Article
Language:English
Published: 2024
Subjects:
Engineering
Additive manufacturing
In-situ monitoring
Online Access:https://hdl.handle.net/10356/180840

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