Machine learning applied to property prediction of metal additive manufacturing products with textural features extraction-Reference-Cited by-同舟云学术

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Machine learning applied to property prediction of metal additive manufacturing products with textural features extraction

Published:2024-03-06 Issue:1-2 Volume:132 Page:83-98
ISSN:0268-3768
Container-title:The International Journal of Advanced Manufacturing Technology
language:en
Short-container-title:Int J Adv Manuf Technol

Author:

Chang Lien-Kai,Chen Ri-Sheng,Tsai Mi-Ching,Lee Rong-Mao,Lin Ching-Chih,Huang Jhih-Cheng,Chang Tsung-Wei,Horng Ming-Huwi

Funder

National Science and Technology Council

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00170-024-13165-y.pdf

Reference38 articles.

1. Felice IO, Shen J, Barragan AF, Moura IA, Li B, Wang B et al (2023) Wire and arc additive manufacturing of Fe-based shape memory alloys: microstructure, mechanical and functional behavior. Mater Des 231:112004. https://doi.org/10.1016/j.matdes.2023.112004

2. Marques DA, Oliveira JP, Baptista AC (2023) A short review on the corrosion behaviour of wire and arc additive manufactured materials. Metals 13(4):641. https://doi.org/10.3390/met13040641

3. Hamilton RF, Bimber BA, Palmer TA (2018) Correlating microstructure and superelasticity of directed energy deposition additive manufactured Ni-rich NiTi alloys. J Alloys Compd 739:712–722. https://doi.org/10.1016/j.jallcom.2017.12.270

4. Wang C, Tan XP, Du Z, Chandra S, Sun Z, Lim CWJ et al (2019) Additive manufacturing of NiTi shape memory alloys using pre-mixed powders. J Mater Process Technol 271:152–161. https://doi.org/10.1016/j.jmatprotec.2019.03.025

5. Li B, Wang L, Wang B, Li D, Oliveira JP, Cui R et al (2022) Electron beam freeform fabrication of NiTi shape memory alloys: crystallography, martensitic transformation, and functional response. Mater Sci Eng A 843:143135. https://doi.org/10.1016/j.msea.2022.143135

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