Machine learning-assisted acoustic emission monitoring for track formability prediction of laser powder bed fusion-Reference-Cited by-同舟云学术

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Machine learning-assisted acoustic emission monitoring for track formability prediction of laser powder bed fusion

Published:2024-03 Issue: Volume:38 Page:108522
ISSN:2352-4928
Container-title:Materials Today Communications
language:en
Short-container-title:Materials Today Communications

Author:

Wang Haijie,Zhang Saifan,Li Bo

Funder

Science and Technology Commission of Shanghai Municipality

National Natural Science Foundation of China

Natural Science Foundation of Shanghai Municipality

Publisher

Elsevier BV

Reference32 articles.

1. Optical interconnects on a flexible substrate by multi-material hybrid additive and subtractive manufacturing;Tipton;Addit. Manuf.,2021

2. Additive manufacturing of NiTi-Ti6Al4V multi-material cellular structures targeting orthopedic implants;Bartolomeu;Opt. Lasers Eng.,2020

3. A market assessment of additive manufacturing potential for the aerospace industry;Altıparmak;J. Manuf. Process.,2021

4. Tribological and mechanical behavior of AISI 316L lattice-supported structures produced by laser powder-bed fusion;Yasa;Int. J. Adv. Manuf. Technol.,2022

5. Monitoring molten pool temperature, grain size and molten pool plasma with integrated area of the spectrum during laser additive manufacturing;Hu;J. Manuf. Process.,2021

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