A machine learning guided investigation of quality repeatability in metal laser powder bed fusion additive manufacturing
Additive manufacturing has entered the phase of industrial adoption, for which its quality repeatability is of vital importance to industries where functional parts with consistent mechanical properties are desired. This concern will manifest with large scale implementation of such technology, affec...
Saved in:
Main Authors: | Huang, De Jun, Li, Hua |
---|---|
Other Authors: | School of Mechanical and Aerospace Engineering |
Format: | Article |
Language: | English |
Published: |
2021
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/154118 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Laser powder bed fusion for metal additive manufacturing: perspectives on recent developments
by: Sing, Swee Leong, et al.
Published: (2021) -
Perspectives of using machine learning in laser powder bed fusion for metal additive manufacturing
by: Sing, Swee Leong, et al.
Published: (2021) -
Emerging metallic systems for additive manufacturing : in-situ alloying and multi-metal processing in laser powder bed fusion
by: Sing, Swee Leong, et al.
Published: (2021) -
Laser powder bed fusion of titanium-tantalum alloys : compositions and designs for biomedical applications
by: Huang, Sheng, et al.
Published: (2021) -
Encoding data into metal alloys using laser powder bed fusion
by: Sofinowski, Karl, et al.
Published: (2022)