Machine learning for additive manufacturing: Predicting materials characteristics and their uncertainty

Machine learning for additive manufacturing: Predicting materials characteristics and their uncertainty

Additive manufacturing (AM) is known for versatile fabrication of complex parts, while also allowing the synthesis of materials with desired microstructures and resulting properties. These benefits come at a cost: process control to manufacture parts within given specifications is very challenging d...

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Bibliographic Details
Main Authors: Dmitry Chernyavsky, Denys Y. Kononenko, Jun Hee Han, Hwi Jun Kim, Jeroen van den Brink, Konrad Kosiba
Format: Article
Language:English
Published: Elsevier 2023-03-01
Series:Materials & Design
Subjects:
Additive manufacturing
Laser powder bed fusion
Machine learning
Gaussian processes
Metallic glass
Uncertainty quantification
Online Access:http://www.sciencedirect.com/science/article/pii/S0264127523001144

Internet

http://www.sciencedirect.com/science/article/pii/S0264127523001144

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