Digital Twin for maintenance: A literature review

I Errandonea, S Beltrán, S Arrizabalaga - Computers in Industry, 2020 - Elsevier
Abstract In recent years, Digital Twins (DT) have been implemented in different industrial
sectors, in several applications areas such as design, production, manufacturing, and …

Data fusion and machine learning for industrial prognosis: Trends and perspectives towards Industry 4.0

A Diez-Olivan, J Del Ser, D Galar, B Sierra - Information Fusion, 2019 - Elsevier
The so-called “smartization” of manufacturing industries has been conceived as the fourth
industrial revolution or Industry 4.0, a paradigm shift propelled by the upsurge and …

Recent advances in prognostics and health management for advanced manufacturing paradigms

T **a, Y Dong, L **ao, S Du, E Pan, L ** - Reliability Engineering & System …, 2018 - Elsevier
Manufacturing paradigms have played their important roles in modern industry. In recent 20
years, production systems of advanced manufacturing paradigms (eg mass customization …

A generalized remaining useful life prediction method for complex systems based on composite health indicator

P Wen, S Zhao, S Chen, Y Li - Reliability Engineering & System Safety, 2021 - Elsevier
As one of the key techniques in Prognostics and Health Management (PHM), accurate
Remaining Useful Life (RUL) prediction can effectively reduce the number of downtime …

Multimodal data fusion for systems improvement: A review

N Gaw, S Yousefi, MR Gahrooei - … from the Air Force Institute of …, 2022 - taylorfrancis.com
In recent years, information available from multiple data modalities has become increasingly
common for industrial engineering and operations research applications. There have been a …

Construction theory for a building intelligent operation and maintenance system based on digital twins and machine learning

Y Zhao, N Wang, Z Liu, E Mu - Buildings, 2022 - mdpi.com
The operation and maintenance (O&M) of buildings plays an important role in ensuring that
the buildings work normally, as well as reducing the damage caused by functional errors …

A deep reinforcement learning approach for real-time sensor-driven decision making and predictive analytics

E Skordilis, R Moghaddass - Computers & Industrial Engineering, 2020 - Elsevier
The increased complexity of sensor-intensive systems with expensive subsystems and
costly repairs and failures calls for efficient real-time control and decision making policies …

[HTML][HTML] Modernizing risk assessment: A systematic integration of PRA and PHM techniques

R Moradi, KM Groth - Reliability Engineering & System Safety, 2020 - Elsevier
Recent advances in sensing and computing technologies have resulted in an abundance of
data in various formats and more processing power for using this data. Consequently, there …

Multistream sensor fusion-based prognostics model for systems with single failure modes

X Fang, K Paynabar, N Gebraeel - Reliability Engineering & System Safety, 2017 - Elsevier
Advances in sensor technology have facilitated the capability of monitoring the degradation
of complex engineering systems through the analysis of multistream degradation signals …

Statistical degradation modeling and prognostics of multiple sensor signals via data fusion: A composite health index approach

C Song, K Liu - IISE Transactions, 2018 - Taylor & Francis
Nowadays multiple sensors are widely used to simultaneously monitor the degradation
status of a unit. Because those sensor signals are often correlated and measure different …