Vol. 4 No. 2 (2024): Journal of AI-Assisted Scientific Discovery
Articles

AI-Based Predictive Maintenance Solutions for U.S. Aerospace Manufacturing: Techniques and Real-World Applications

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  • Dr. Marie Dubois
Dr. Marie Dubois
Professor of Mathematics and Computer Science, Université catholique de Louvain, Belgium
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Published 23-08-2024

Keywords

  • Predictive Maintenance,
  • Aerospace Manufacturing
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.

How to Cite

[1]
Dr. Marie Dubois, “AI-Based Predictive Maintenance Solutions for U.S. Aerospace Manufacturing: Techniques and Real-World Applications”, Journal of AI-Assisted Scientific Discovery, vol. 4, no. 2, pp. 94–123, Aug. 2024, Accessed: Nov. 14, 2024. [Online]. Available: https://scienceacadpress.com/index.php/jaasd/article/view/152

Abstract

In the United States, the aerospace products and parts manufacturing industry is one of the most advanced industries, with 56% of R&D expenses accounting for USD 32,064 million in 2022. For the industry, the U.S. ranked number one in 2019 by contribution of the aviation industry to GDP, according to Pew Research Center. Today, the United States is home to the world's largest civil aviation system. There were 5,080 public airports in the United States as of 2018. Technology evolution is also driving growth in the aerospace industry. In 2021, AWS, Google, and IBM broke into the cloud computing space, focusing primarily on aerospace. In recent years, production milestones have been achieved in delivering raw materials, parts, and assemblies for next-generation innovative new, under-development aircraft. New technologies, such as advanced lightweight composites, complex additively manufactured metal parts, advanced propulsion systems, advanced jet engine manufacturing technologies, and digital thread and digital twin methodologies for parts, performance, and process analysis, are being incorporated.

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