Predictive maintenance in Industry 4.0: A systematic multi-sector map**

P Mallioris, E Aivazidou, D Bechtsis - CIRP Journal of Manufacturing …, 2024‏ - Elsevier
Industry 4.0 is strongly intertwined with big data streaming flows from intelligent sensors and
machinery installed in industrial facilities. Failures can disrupt production and lead the …

Attention-based deep meta-transfer learning for few-shot fine-grained fault diagnosis

C Li, S Li, H Wang, F Gu, AD Ball - Knowledge-based systems, 2023‏ - Elsevier
Deep learning-based fault diagnosis methods have made tremendous progress in recent
years; however, most of these methods are coarse grained and data demanding that cannot …

[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 …

[HTML][HTML] Alarm-based predictive maintenance scheduling for aircraft engines with imperfect Remaining Useful Life prognostics

I De Pater, A Reijns, M Mitici - Reliability Engineering & System Safety, 2022‏ - Elsevier
The increasing availability of condition monitoring data for aircraft components has
incentivized the development of Remaining Useful Life (RUL) prognostics in the past years …

Hyperparameter-optimized multi-fidelity deep neural network model associated with subset simulation for structural reliability analysis

JPS Lima, F Evangelista Jr, CG Soares - Reliability Engineering & System …, 2023‏ - Elsevier
The present study proposes a two-stage Bi-Fidelity Deep Neural Network surrogate model to
quantify the uncertainty of structural analysis using low-fidelity data samples added to the …

Adaptive directed support vector machine method for the reliability evaluation of aeroengine structure

C Li, JR Wen, J Wan, O Taylan, CW Fei - Reliability Engineering & System …, 2024‏ - Elsevier
Abstract Machine learning methods have been widely applied to structural reliability
analysis, due to the excellent performance in modeling precision and efficiency. In this …

Determination of Conditions to Provide Transport Logistics Support Service to Aircraft at Aerodromes in Ukraine

O Kalinichenko, O Pavlenko, Y Nagornyy… - … Conference on Smart …, 2023‏ - Springer
The transport logistics support service of aircraft is a very complex technology. The
aspiration of Ukraine for NATO standards in servicing military aircraft and the expansion of …

A dynamic predictive maintenance approach using probabilistic deep learning for a fleet of multi-component systems

J Zeng, Z Liang - Reliability Engineering & System Safety, 2023‏ - Elsevier
Empowered by the ubiquitous sensing infrastructure, predictive maintenance (PdM) has
received increasing attention. However, designing predictive maintenance for multiple …

Maximizing robustness of aircraft routing with heterogeneous maintenance tasks

Y He, HL Ma, WY Park, SQ Liu, SH Chung - Transportation Research Part …, 2023‏ - Elsevier
In aircraft maintenance routing, the disruption caused by the stochasticity of the maintenance
duration is a critical challenge. Previous studies considered the sources of disruptions in an …

Hierarchical Bayesian support vector regression with model parameter calibration for reliability modeling and prediction

S Haoyuan, M Yizhong, L Chenglong, Z Jian… - Reliability Engineering & …, 2023‏ - Elsevier
Support vector regression (SVR) has been widely used for reliability modeling and
prediction in various engineering practices. In order to improve the accuracy and robustness …