[HTML][HTML] Explainable AI in manufacturing and industrial cyber–physical systems: a survey
S Moosavi, M Farajzadeh-Zanjani, R Razavi-Far… - Electronics, 2024 - mdpi.com
This survey explores applications of explainable artificial intelligence in manufacturing and
industrial cyber–physical systems. As technological advancements continue to integrate …
industrial cyber–physical systems. As technological advancements continue to integrate …
Constructing explainable health indicators for aircraft engines by developing an interpretable neural network with discretized weights
Remaining useful life predictions depend on the quality of health indicators (HIs) generated
from condition monitoring sensors, evaluated by predefined prognostic metrics such as …
from condition monitoring sensors, evaluated by predefined prognostic metrics such as …
A Survey of Transformer Enabled Time Series Synthesis
Generative AI has received much attention in the image and language domains, with the
transformer neural network continuing to dominate the state of the art. Application of these …
transformer neural network continuing to dominate the state of the art. Application of these …
Research on risk management of ship maintenance projects based on multi agent swarm model simulation method
K Wang, P Dong, W Chen, R Ma, L Cui - Heliyon, 2024 - cell.com
In recent years, the role of naval ship power has become increasingly prominent in regional
conflicts and military operations worldwide, and the powerful capabilities demonstrated by …
conflicts and military operations worldwide, and the powerful capabilities demonstrated by …
Explainable Anomaly Detection: Counterfactual driven What-If Analysis
There exists three main areas of study inside of the field of predictive maintenance: anomaly
detection, fault diagnosis, and remaining useful life prediction. Notably, anomaly detection …
detection, fault diagnosis, and remaining useful life prediction. Notably, anomaly detection …
The research landscape of industry 5.0: a scientific mapping based on bibliometric and topic modeling techniques
A Rejeb, K Rejeb, I Zrelli, Y Kayikci… - Flexible Services and …, 2024 - Springer
Abstract Industry 5.0 (I5. 0) marks a transformative shift toward integrating advanced
technologies with human-centric design to foster innovation, resilient manufacturing, and …
technologies with human-centric design to foster innovation, resilient manufacturing, and …
Interpretable Prognostics with Concept Bottleneck Models
Deep learning approaches have recently been extensively explored for the prognostics of
industrial assets. However, they still suffer from a lack of interpretability, which hinders their …
industrial assets. However, they still suffer from a lack of interpretability, which hinders their …
ML-Based Maintenance and Control Process Analysis, Simulation, and Automation—A Review.
Automation and digitalization in various industries towards the Industry 4.0/5.0 paradigms
are rapidly progressing thanks to the use of sensors, Industrial Internet of Things (IIoT), and …
are rapidly progressing thanks to the use of sensors, Industrial Internet of Things (IIoT), and …
[HTML][HTML] Predictive maintenance in Industry 4.0: a survey of planning models and machine learning techniques
I Hector, R Panjanathan - PeerJ Computer Science, 2024 - peerj.com
Equipment downtime resulting from maintenance in various sectors around the globe has
become a major concern. The effectiveness of conventional reactive maintenance methods …
become a major concern. The effectiveness of conventional reactive maintenance methods …
A Survey on Predictive Maintenance in the Maritime Industry Using Machine and Federated Learning
The maritime industry is responsible for the transportation of over 80% of worldwide
commodities. Currently, the industry heavily relies on traditional maintenance strategies …
commodities. Currently, the industry heavily relies on traditional maintenance strategies …