TY - JOUR
T1 - Prediction of remaining useful life using the CNN-GRU network
T2 - A study on maintenance management[Formula presented]
AU - Azyus, Adryan Fitra
AU - Wijaya, Sastra Kusuma
AU - Naved, Mohd
N1 - Publisher Copyright:
© 2023 The Author(s)
PY - 2023/9
Y1 - 2023/9
N2 - The CNN-GRU network is an open-source software package for predicting the remaining useful lives (RULs) of systems and components using advanced deep learning techniques. Adopted across various industries, this software enables more accurate and efficient RUL prediction, facilitating data-driven maintenance decisions. This paper discusses ongoing research, limitations, and future improvements aimed at enhancing the software's accuracy, efficiency, and applicability.
AB - The CNN-GRU network is an open-source software package for predicting the remaining useful lives (RULs) of systems and components using advanced deep learning techniques. Adopted across various industries, this software enables more accurate and efficient RUL prediction, facilitating data-driven maintenance decisions. This paper discusses ongoing research, limitations, and future improvements aimed at enhancing the software's accuracy, efficiency, and applicability.
KW - Accuracy and efficiency
KW - Convolutional neural networks (CNNs)
KW - Cross-industry applications
KW - Gated recurrent unit (GRU)
KW - Predictive maintenance
KW - Remaining useful life (RUL)
UR - http://www.scopus.com/inward/record.url?scp=85164525982&partnerID=8YFLogxK
U2 - 10.1016/j.simpa.2023.100535
DO - 10.1016/j.simpa.2023.100535
M3 - Article
AN - SCOPUS:85164525982
SN - 2665-9638
VL - 17
JO - Software Impacts
JF - Software Impacts
M1 - 100535
ER -