Data fusion and machine learning for industrial prognosis: Trends and perspectives towards Industry 4.0
The so-called “smartization” of manufacturing industries has been conceived as the fourth
industrial revolution or Industry 4.0, a paradigm shift propelled by the upsurge and …
industrial revolution or Industry 4.0, a paradigm shift propelled by the upsurge and …
Machinery health prognostics: A systematic review from data acquisition to RUL prediction
Machinery prognostics is one of the major tasks in condition based maintenance (CBM),
which aims to predict the remaining useful life (RUL) of machinery based on condition …
which aims to predict the remaining useful life (RUL) of machinery based on condition …
Towards multi-model approaches to predictive maintenance: A systematic literature survey on diagnostics and prognostics
The use of a modern technological system requires a good engineering approach,
optimized operations, and proper maintenance in order to keep the system in an optimal …
optimized operations, and proper maintenance in order to keep the system in an optimal …
Remaining useful life estimation via transformer encoder enhanced by a gated convolutional unit
Abstract Remaining Useful Life (RUL) estimation is a fundamental task in the prognostic and
health management (PHM) of industrial equipment and systems. To this end, we propose a …
health management (PHM) of industrial equipment and systems. To this end, we propose a …
An integrated method of the future capacity and RUL prediction for lithium-ion battery pack
C Zhang, S Zhao, Y He - IEEE Transactions on Vehicular …, 2021 - ieeexplore.ieee.org
Accurate prediction of remaining useful life (RUL) is of critical significance to the safety and
reliability of lithium-ion batteries, which can offer efficient early warning signals for failure …
reliability of lithium-ion batteries, which can offer efficient early warning signals for failure …
A review of the application of machine learning and data mining approaches in continuum materials mechanics
Machine learning tools represent key enablers for empowering material scientists and
engineers to accelerate the development of novel materials, processes and techniques. One …
engineers to accelerate the development of novel materials, processes and techniques. One …
Feature extraction for data-driven remaining useful life prediction of rolling bearings
H Zhao, H Liu, Y Jin, X Dang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
A variety of data-driven methods have been proposed to predict remaining useful life (RUL)
of key component for rolling bearings. The accuracy of data-driven RUL prediction model …
of key component for rolling bearings. The accuracy of data-driven RUL prediction model …
A new dynamic predictive maintenance framework using deep learning for failure prognostics
KTP Nguyen, K Medjaher - Reliability Engineering & System Safety, 2019 - Elsevier
Abstract In Prognostic Health and Management (PHM) literature, the predictive maintenance
studies can be classified into two groups. The first group focuses on the prognostics step but …
studies can be classified into two groups. The first group focuses on the prognostics step but …
From corrective to predictive maintenance—A review of maintenance approaches for the power industry
M Molęda, B Małysiak-Mrozek, W Ding, V Sunderam… - Sensors, 2023 - mdpi.com
Appropriate maintenance of industrial equipment keeps production systems in good health
and ensures the stability of production processes. In specific production sectors, such as the …
and ensures the stability of production processes. In specific production sectors, such as the …
A directed acyclic graph network combined with CNN and LSTM for remaining useful life prediction
Accurate and timely prediction of remaining useful life (RUL) of a machine enables the
machine to have an appropriate operation and maintenance decision. Data-driven RUL …
machine to have an appropriate operation and maintenance decision. Data-driven RUL …