The aviation industry faces various challenges in meeting long-term sustainability goals
amidst surging demand for air travel and growing environmental concerns of the general …

Prognostic and health management (PHM) plays a vital role in ensuring the safety and
reliability of aircraft systems. The process entails the proactive surveillance and evaluation of …

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 …

Abstract Researches on Remaining Useful Life (RUL) prediction of aero-engine could help
to make maintenance plans, improve operation reliabilities and reduce maintenance costs …

Abstract Prognostic Health Management aims to predict the Remaining Useful Life (RUL) of
degrading components/systems utilizing monitoring data. These RUL predictions form the …

This paper presents a model for optimising fleet maintenance management with a particular
application to train rolling stock fleets. The proposed model produces a joint schedule for …

Trustworthy remaining useful life (RUL) predictions are critical for the long-term safe and
reliable operation of degradation systems. The existing deep learning-based methods for …

In data-driven prognostics and health management (PHM), most studies focus only on
prognostics performance but rarely consider maintenance decision problems. However …

Reliable prediction of the remaining useful life (RUL) is important for improving maintenance
efficiency, equipment availability, and avoiding catastrophic accidents in complex industrial …

Remaining useful life predictions depend on the quality of health indicators (HIs) generated
from condition monitoring sensors, evaluated by predefined prognostic metrics such as …