A review of machine learning techniques for process and performance optimization in laser beam powder bed fusion additive manufacturing-Reference-Cited by-同舟云学术

A review of machine learning techniques for process and performance optimization in laser beam powder bed fusion additive manufacturing

Published:2022-09-15 Issue: Volume: Page:
ISSN:0956-5515
Container-title:Journal of Intelligent Manufacturing
language:en
Short-container-title:J Intell Manuf

Author:

Liu Jia^ORCID,Ye Jiafeng,Silva Izquierdo Daniel,Vinel Aleksandr,Shamsaei Nima,Shao Shuai

Funder

Federal Aviation Administration

National Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Industrial and Manufacturing Engineering,Software

Link

https://link.springer.com/content/pdf/10.1007/s10845-022-02012-0.pdf

Reference109 articles.

1. “Additive Manufacturing Market by Technology” AMPOWER Report2020, Available: https://additive-manufacturing-report.com/additive-manufacturing-market/. Accessed Nov 2020.

2. “Broad Agency Announcement, Explainable Artificial Intelligence (XAI),” Defense Advanced Research Projects Agency, DARPA-BAA-16–53 (DARPA, 2016), 2016. https://www.darpa.mil/attachments/DARPA-BAA-16-53.pdf. Accessed Nov 2020.

3. Aboulkhair, N. T., Everitt, N. M., Ashcroft, I., & Tuck, C. (2014). Reducing porosity in AlSi10Mg parts processed by selective laser melting. Additive Manufacturing, 1–4, 77–86.

4. Adadi, A., & Berrada, M. (2018). Peeking inside the black-box: A survey on explainable artificial intelligence (XAI). IEEE Access, 6, 52138–52160.

5. Aoyagi, K., Wang, H., Sudo, H., & Chiba, A. (2019). Simple method to construct process maps for additive manufacturing using a support vector machine. Additive Manufacturing, 27, 353–362.

Cited by 31 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Data-driven modeling of process-structure-property relationships in metal additive manufacturing;npj Advanced Manufacturing;2024-09-12

2. Pulse approach: a physics-guided machine learning model for thermal analysis in laser-based powder bed fusion of metals;Progress in Additive Manufacturing;2024-07-26

3. High-Throughput Microstructural Characterization and Process Correlation Using Automated Electron Backscatter Diffraction;Integrating Materials and Manufacturing Innovation;2024-06-28

4. Laser Powder Bed Fusion of Ti-6Al-4 V Alloys for the Production of Defect-Free AM Parts: A Recent Update;Lasers in Manufacturing and Materials Processing;2024-05-11

5. Effects and mechanisms of rare earth and calcium on the flame retardancy of magnesium alloys;Journal of Materials Research and Technology;2024-05