Laser powder bed fusion for AI assisted digital metal components-Reference-Cited by-同舟云学术

Laser powder bed fusion for AI assisted digital metal components

Published:2022-05-05 Issue:4 Volume:17 Page:806-820
ISSN:1745-2759
Container-title:Virtual and Physical Prototyping
language:en
Short-container-title:Virtual and Physical Prototyping

Author:

Seo Eunhyeok¹^ORCID,Sung Hyokyung²^ORCID,Jeon Hongryoung¹,Kim Hayeol¹,Kim Taekyeong¹,Park Sangeun²,Lee Min Sik¹,Moon Seung Ki³,Kim Jung Gi²,Chung Hayoung¹,Choi Seong-Kyum⁴,Yu Ji-Hun⁵,Kim Kyung Tae⁵,Park Seong Jin⁶,Kim Namhun¹,Jung Im Doo¹^ORCID

Affiliation:

1. Department of Mechanical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea

2. Department of Materials Engineering and Convergence Technology, Gyeongsang National University, Jinju, Republic of Korea

3. School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore

4. G.W.W. School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA

5. Powder & Ceramic Materials Division, Korea Institute of Materials Science, Changwon, Republic of Korea

6. Department of Mechanical Engineering, Pohang University of Science and Technology, Pohang, Republic of Korea

Funder

National Research Foundation of Korea

Korea government

MSIT

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Computer Graphics and Computer-Aided Design,Modeling and Simulation,Signal Processing

Link

https://www.tandfonline.com/doi/pdf/10.1080/17452759.2022.2068804

Reference44 articles.

1. Applications of Wireless Sensor Networks in the Oil, Gas and Resources Industries

2. Using wireless sensor networks to enable increased oil recovery

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4. Columbus, Louis. 2020. “10 Ways AI Is Improving Manufacturing In 2020.” Forbes. https://www.forbes.com/sites/louiscolumbus/2020/05/18/10-ways-ai-is-improving-manufacturing-in-2020/?sh=d00dc2c1e85a.

5. Metallurgy, mechanistic models and machine learning in metal printing

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