On predictive maintenance in industry 4.0: Overview, models, and challenges

M Achouch, M Dimitrova, K Ziane… - Applied Sciences, 2022 - mdpi.com
In the era of the fourth industrial revolution, several concepts have arisen in parallel with this
new revolution, such as predictive maintenance, which today plays a key role in sustainable …

A prognostic driven predictive maintenance framework based on Bayesian deep learning

L Zhuang, A Xu, XL Wang - Reliability Engineering & System Safety, 2023 - Elsevier
Recent years have witnessed prominent advances in predictive maintenance (PdM) for
complex industrial systems. However, the existing PdM literature predominately separates …

[HTML][HTML] Deep reinforcement learning for predictive aircraft maintenance using probabilistic remaining-useful-life prognostics

J Lee, M Mitici - Reliability Engineering & System Safety, 2023 - Elsevier
The increasing availability of sensor monitoring data has stimulated the development of
Remaining-Useful-Life (RUL) prognostics and maintenance planning models. However …

An overview of the state of the art in aircraft prognostic and health management strategies

M Kordestani, ME Orchard… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Aircraft are complex engineering systems composed of many interconnected subsystems
with possible uncertainties in their structure. They often function for a long number of flight …

[HTML][HTML] Dynamic predictive maintenance for multiple components using data-driven probabilistic RUL prognostics: The case of turbofan engines

M Mitici, I de Pater, A Barros, Z Zeng - Reliability Engineering & System …, 2023 - Elsevier
The increasing availability of condition-monitoring data for components/systems has
incentivized the development of data-driven Remaining Useful Life (RUL) prognostics in the …

Remaining useful life prediction of aero-engine enabled by fusing knowledge and deep learning models

Y Li, Y Chen, Z Hu, H Zhang - Reliability Engineering & System Safety, 2023 - Elsevier
The remaining useful life (RUL) prediction of a complex engineering system is extremely
significant for ensuring system reliability. The conventional prediction of the RUL based on …

Optimizing prior distribution parameters for probabilistic prediction of remaining useful life using deep learning

Y Keshun, Q Guangqi, G Yingkui - Reliability Engineering & System Safety, 2024 - Elsevier
In this study, a deep learning-based probabilistic remaining useful life (RUL) prediction
model is proposed to improve the strong prior limitations of traditional probabilistic RUL …

[HTML][HTML] Developing health indicators and RUL prognostics for systems with few failure instances and varying operating conditions using a LSTM autoencoder

I de Pater, M Mitici - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
Abstract Most Remaining Useful Life (RUL) prognostics are obtained using supervised
learning models trained with many labelled data samples (ie, the true RUL is known). In …

Spatial correlation and temporal attention-based LSTM for remaining useful life prediction of turbofan engine

H Tian, L Yang, B Ju - Measurement, 2023 - Elsevier
Remaining useful life (RUL) prediction has always been a core task of prognostics and
health management technology, which is crucial to the reliable and safe operation of …

A hybrid CNN-LSTM model for joint optimization of production and imperfect predictive maintenance planning

HD Shoorkand, M Nourelfath, A Hajji - Reliability Engineering & System …, 2024 - Elsevier
This paper deals with the problem of dynamically integrating tactical production planning
and predictive maintenance in the context of a rolling horizon approach. At the production …