Data-Driven Remaining Useful Life Estimation for Milling Process: Sensors, Algorithms, Datasets, and Future Directions.
Sameer SayyadSatish KumarArunkumar M. BongalePooja KamatShruti PatilKetan KotechaPublished in: IEEE Access (2021)
Keyphrases
- future directions
- data driven
- lessons learned
- benchmark datasets
- synthetic and real datasets
- learning algorithm
- optimization problems
- computationally efficient
- data structure
- real and synthetic datasets
- real time
- current trends
- significant improvement
- uci machine learning repository
- current challenges
- current status
- tool wear
- data fusion
- sampling methods
- black box
- sensor data
- computational complexity
- real world