An efficient deep learning prognostic model for remaining useful life estimation of high speed CNC milling machine cutters
CNC machines are engaged in numerous industries, including critical ones like the aerospace, automotive, and military sectors, among others. Sensor data are time-series that may suffer from complex interconnections between variables and dynamic features. Long Short Term Memory LSTM excels in dynamic...
Saved in:
| Main Authors: | Hamdy K. Elminir, Mohamed A. El-Brawany, Dina Adel Ibrahim, Hatem M. Elattar, E.A. Ramadan |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
|
| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123024016724 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Perbandingan pembuatan produk menggunakan simulasi program CNC dan CNC Milling
by: Hendra -, et al.
Published: (2022-04-01) -
Investigation of the Applicability of Acoustic Emission Signals for Adaptive Control in CNC Wood Milling
by: Miroslav Dado, et al.
Published: (2025-06-01) -
Stabilization of Contour Milling on CNC Machines
by: Yuri Petrakov, et al.
Published: (2025-02-01) -
BLTTNet: feature fusion based on BiLSTM-Transfomer-TCN for prediction of remaining useful life of aircraft engines
by: Yixu Yang, et al.
Published: (2025-07-01) -
Initialization of cutting tools and milling paths for 5-axis CNC flank milling of freeform surfaces
by: Pengbo Bo, et al.
Published: (2025-06-01)