A comprehensive review of digital twin—part 1: modeling and twinning enabling technologies
As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented
attention because of its promise to further optimize process design, quality control, health …
attention because of its promise to further optimize process design, quality control, health …
Transfer learning algorithms for bearing remaining useful life prediction: A comprehensive review from an industrial application perspective
Accurate remaining useful life (RUL) prediction for rolling bearings encounters many
challenges such as complex degradation processes, varying working conditions, and …
challenges such as complex degradation processes, varying working conditions, and …
Prognostics and Health Management (PHM): Where are we and where do we (need to) go in theory and practice
E Zio - Reliability Engineering & System Safety, 2022 - Elsevier
We are performing the digital transition of industry, living the 4th industrial revolution,
building a new World in which the digital, physical and human dimensions are interrelated in …
building a new World in which the digital, physical and human dimensions are interrelated in …
Multi-scale integrated deep self-attention network for predicting remaining useful life of aero-engine
Remaining useful life (RUL) prediction is the core research task of aero-engine prognostics
health management (PHM), which is crucial to promoting the safety, reliability and economy …
health management (PHM), which is crucial to promoting the safety, reliability and economy …
The emerging graph neural networks for intelligent fault diagnostics and prognostics: A guideline and a benchmark study
Deep learning (DL)-based methods have advanced the field of Prognostics and Health
Management (PHM) in recent years, because of their powerful feature representation ability …
Management (PHM) in recent years, because of their powerful feature representation ability …
FGDAE: A new machinery anomaly detection method towards complex operating conditions
Recent studies on machinery anomaly detection only based on normal data training models
have yielded good results in improving operation reliability. However, most of the studies …
have yielded good results in improving operation reliability. However, most of the studies …
[HTML][HTML] Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry
A Theissler, J Pérez-Velázquez, M Kettelgerdes… - Reliability engineering & …, 2021 - Elsevier
Recent developments in maintenance modelling fueled by data-based approaches such as
machine learning (ML), have enabled a broad range of applications. In the automotive …
machine learning (ML), have enabled a broad range of applications. In the automotive …
Prediction of remaining useful life based on bidirectional gated recurrent unit with temporal self-attention mechanism
Prediction of remaining useful life (RUL) is of vital significance in the prognostics health
management (PHM) tasks. To deal with the reverse time series and to reflect the difference …
management (PHM) tasks. To deal with the reverse time series and to reflect the difference …
A prognostic driven predictive maintenance framework based on Bayesian deep learning
Recent years have witnessed prominent advances in predictive maintenance (PdM) for
complex industrial systems. However, the existing PdM literature predominately separates …
complex industrial systems. However, the existing PdM literature predominately separates …
Machine learning for reliability engineering and safety applications: Review of current status and future opportunities
Abstract Machine learning (ML) pervades an increasing number of academic disciplines and
industries. Its impact is profound, and several fields have been fundamentally altered by it …
industries. Its impact is profound, and several fields have been fundamentally altered by it …