Leveraging Machine Learning for Predictive Analytics in U.S. Aerospace Manufacturing: Techniques and Case Studies

Authors

  • Dr. Krzysztof Kowalski Associate Professor of Computer Science, Warsaw University of Technology, Poland Author

Keywords:

Predictive Analytics, Aerospace Manufacturing

Abstract

Aerospace manufacturing provides a real-world, high-stakes environment to experiment with predictive analytics, and more broadly in leveraging machine learning. The need to reduce dependence on legacy algorithms and manual operations in order to integrate machine learning into predictive analytics drives the motivation of this paper. We present a comprehensive review of the applications of a variety of machine learning algorithms within the context of aerospace manufacturing. Through this, we summarize the body of existing work and provide a detailed account of other successful approaches to the application of deep learning within predictive analytics.

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Published

28-08-2024

How to Cite

[1]
Dr. Krzysztof Kowalski, “Leveraging Machine Learning for Predictive Analytics in U.S. Aerospace Manufacturing: Techniques and Case Studies”, J. of Artificial Int. Research and App., vol. 4, no. 2, pp. 153–178, Aug. 2024, Accessed: Dec. 23, 2024. [Online]. Available: https://aimlstudies.co.uk/index.php/jaira/article/view/236

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