[PDF][PDF] A survey of predictive maintenance: Systems, purposes and approaches

Y Ran, X Zhou, P Lin, Y Wen… - arxiv preprint arxiv …, 2019 - researchgate.net
This paper provides a comprehensive literature review on Predictive Maintenance (PdM)
with emphasis on system architectures, purposes and approaches. In industry, any outages …

Prognostics and health management of industrial assets: Current progress and road ahead

L Biggio, I Kastanis - Frontiers in Artificial Intelligence, 2020 - frontiersin.org
Prognostic and Health Management (PHM) systems are some of the main protagonists of
the Industry 4.0 revolution. Efficiently detecting whether an industrial component has …

Multicellular LSTM-based deep learning model for aero-engine remaining useful life prediction

S **ang, Y Qin, J Luo, H Pu, B Tang - Reliability Engineering & System …, 2021 - Elsevier
The prediction of aero-engine remaining useful life (RUL) is helpful for its operation and
maintenance. Aiming at the challenge that most neural networks (NNs), including long short …

Artificial intelligence in prognostics and health management of engineering systems

S Ochella, M Shafiee, F Dinmohammadi - Engineering Applications of …, 2022 - Elsevier
Prognostics and health management (PHM) has become a crucial aspect of the
management of engineering systems and structures, where sensor hardware and decision …

A review on prognostics methods for engineering systems

J Guo, Z Li, M Li - IEEE Transactions on Reliability, 2019 - ieeexplore.ieee.org
Due to the advancements in sensing technologies and computational capabilities, system
health assessment and prognostics have been extensively investigated in the literature …

Artificial intelligence-based data-driven prognostics in industry: A survey

MA El-Brawany, DA Ibrahim, HK Elminir… - Computers & Industrial …, 2023 - Elsevier
In the age of Industry 5.0, prognostics and health management (PHM) is very important for
proactive and scheduled maintenance in industrial processes. The target of prognosis is the …

Anomaly monitoring improves remaining useful life estimation of industrial machinery

G Aydemir, B Acar - Journal of Manufacturing Systems, 2020 - Elsevier
Estimating remaining useful life (RUL) of industrial machinery based on their degradation
data is very critical for various industries. Machine learning models are powerful and very …

An improved generic hybrid prognostic method for RUL prediction based on PF-LSTM learning

K Xue, J Yang, M Yang, D Wang - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Accurate estimation and prediction of the state-of-health (SOH) and remaining useful life
(RUL) are fundamental to optimal maintenance strategies formulation for prognostics and …

Explainable AI for bearing fault prognosis using deep learning techniques

DC Sanakkayala, V Varadarajan, N Kumar, Karan… - Micromachines, 2022 - mdpi.com
Predicting bearing failures is a vital component of machine health monitoring since bearings
are essential parts of rotary machines, particularly large motor machines. In addition …

A CM&CP framework with a GIACC method and an ensemble model for remaining useful life prediction

Y Li, T Han, T **a, Z Chen, E Pan - Computers in Industry, 2023 - Elsevier
Data-driven methods based on health indicators (HIs) have been proven effective for
remaining useful life (RUL) prediction. Significant differences may exist among HI …