Scalability, Explainability and Performance of Data-Driven Algorithms in Predicting the Remaining Useful Life: A Comprehensive Review
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.
US Army Engineering Research and Develop Center (ERDC) Contract #W912HZ21C0014.
Email Address of Submitting Authorbakhtiaris@gmail.com
ORCID of Submitting Author0000-0002-5230-8723
Submitting Author's InstitutionMississippi State University
Submitting Author's Country
- United States of America