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Scalability_Explainability_and_Performance_of_Data-Driven_Algorithms_in_Predicting_the_Remaining_Useful_Life_A_Comprehensive_Review.pdf (2.99 MB)
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Scalability, Explainability and Performance of Data-Driven Algorithms in Predicting the Remaining Useful Life: A Comprehensive Review

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posted on 2023-05-11, 02:50 authored by Somayeh Bakhtiari RamezaniSomayeh Bakhtiari Ramezani, Logan Cummins, Brad Killen, Richard Carley, Amin Amirlatifi, Shahram Rahimi, Maria Seale, Linkan Bian

This work summarizes the state-of-the-art data-driven methods for prediction of the Remaining Useful Life (RUL). It discusses challenges and open problems faced in PdM. This study presents a discussion on the new problems that need to be considered towards the Industry 4.0 goals. We propose the future direction for each challenge discussed in this article.

Funding

US Army Engineering Research and Develop Center (ERDC) Contract #W912HZ21C0014.

History

Email Address of Submitting Author

bakhtiaris@gmail.com

ORCID of Submitting Author

0000-0002-5230-8723

Submitting Author's Institution

Mississippi State University

Submitting Author's Country

  • United States of America