Nondestructive Quantitative Measurement for Precision Quality Control in Additive Manufacturing Using Hyperspectral Imagery and Machine Learning-Reference-Cited by-同舟云学术

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Nondestructive Quantitative Measurement for Precision Quality Control in Additive Manufacturing Using Hyperspectral Imagery and Machine Learning

Published:2024-08 Issue:8 Volume:20 Page:9963-9975
ISSN:1551-3203
Container-title:IEEE Transactions on Industrial Informatics
language:
Short-container-title:IEEE Trans. Ind. Inf.

Author:

Yan Yijun¹^ORCID,Ren Jinchang¹^ORCID,Sun He²^ORCID,Williams Robert³^ORCID

Affiliation:

1. National Subsea Centre, Robert Gordon University, Aberdeen, U.K.

2. Key Laboratory of Computational Optical Imaging Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China

3. LPW Technology, Ltd., Liverpool, U.K.

Funder

Carpenter Additive, LPW Technology, Ltd.

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/9424/10623532/10510645.pdf?arnumber=10510645

Reference42 articles.

1. 3D printing trends: 2021 predictions;Baldwin,2023

2. Effects of powder recycling on stainless steel powder and built material properties in metal powder bed fusion processes

3. Powder Reuse Cycles in Electron Beam Powder Bed Fusion—Variation of Powder Characteristics

4. The impact of oxidised powder particles on the microstructure and mechanical properties of Ti-6Al-4 V processed by laser powder bed fusion

5. Additive manufacturing of Ti6Al4V alloy: A review

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