Cover Image

State-of-the-art review and synthesis: A requirement-based roadmap for standardized predictive maintenance automation using digital twin technologies

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ma, Sizhe, Flanigan, Katherine A., Bergés, Mario
Format:	Preprint
Published:	2023
Subjects:	Artificial Intelligence Systems and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

State-of-the-Art Review: The Use of Digital Twins to Support Artificial Intelligence-Guided Predictive Maintenance
by: Ma, Sizhe, et al.
Published: (2024)

Digital Twin Technologies in Predictive Maintenance: Enabling Transferability via Sim-to-Real and Real-to-Sim Transfer
by: Ma, Sizhe, et al.
Published: (2025)

Testing predictive automated driving systems: lessons learned and future recommendations
by: Gonzalo, Rubén Izquierdo, et al.
Published: (2022)

A domain adaptation neural network for digital twin-supported fault diagnosis
by: Chen, Zhenling, et al.
Published: (2025)

Can Time-Series Foundation Models Perform Building Energy Management Tasks?
by: Mulayim, Ozan Baris, et al.
Published: (2025)

Convex neural network synthesis for robustness in the 1-norm
by: Drummond, Ross, et al.
Published: (2024)

RUL forecasting for wind turbine predictive maintenance based on deep learning
by: Shah, Syed Shazaib, et al.
Published: (2024)

TwinLab: a framework for data-efficient training of non-intrusive reduced-order models for digital twins
by: Kannapinn, Maximilian, et al.
Published: (2024)

Design of UAV flight state recognition and trajectory prediction system based on trajectory feature construction
by: Zhou, Xingyu, et al.
Published: (2024)

Public and private blockchain for decentralized digital building twins and building automation system
by: Ly, Reachsak, et al.
Published: (2026)

Bridging the Reality Gap in Digital Twins with Context-Aware, Physics-Guided Deep Learning
by: Ma, Sizhe, et al.
Published: (2025)

Learn2Drive: A neural network-based framework for socially compliant automated vehicle control
by: Liu, Yuhui, et al.
Published: (2025)

Optimizing Traffic Signal Control using High-Dimensional State Representation and Efficient Deep Reinforcement Learning
by: Francis, Lawrence, et al.
Published: (2024)

Neural Operator based Reinforcement Learning for Control of first-order PDEs with Spatially-Varying State Delay
by: Hu, Jiaqi, et al.
Published: (2025)

Foundation Models for CPS-IoT: Opportunities and Challenges
by: Baris, Ozan, et al.
Published: (2025)

Mapping back and forth between model predictive control and neural networks
by: Drummond, Ross, et al.
Published: (2024)

Advanced simulation-based predictive modelling for solar irradiance sensor farms
by: Risco-Martín, José L., et al.
Published: (2024)

Planning a Community Approach to Diabetes Care in Low- and Middle-Income Countries Using Optimization
by: Adams, Katherine B., et al.
Published: (2023)

Reinforcement Learning-based Receding Horizon Control using Adaptive Control Barrier Functions for Safety-Critical Systems
by: Sabouni, Ehsan, et al.
Published: (2024)

AI-based framework to predict animal and pen feed intake in feedlot beef cattle
by: Maia, Alex S. C., et al.
Published: (2025)

Customized User Plane Processing via Code Generating AI Agents for Next Generation Mobile Networks
by: Ma, Xiaowen, et al.
Published: (2026)

Task load dependent decision referrals for joint binary classification in human-automation teams
by: Kaza, Kesav, et al.
Published: (2025)

Approximate Information States for Worst-Case Control and Learning in Uncertain Systems
by: Dave, Aditya, et al.
Published: (2023)

On future power system digital twins: A vision towards a standard architecture
by: Zomerdijk, Wouter, et al.
Published: (2024)

Multi-Goal Dexterous Hand Manipulation using Probabilistic Model-based Reinforcement Learning
by: Jiang, Yingzhuo, et al.
Published: (2025)

Meta-Control: Automatic Model-based Control Synthesis for Heterogeneous Robot Skills
by: Wei, Tianhao, et al.
Published: (2024)

Promising and worth-to-try future directions for advancing state-of-the-art surrogates methods of agent-based models in social and health computational sciences
by: Elsheikh, Atiyah
Published: (2024)

Control of Renewable Energy Communities using AI and Real-World Data
by: Fonseca, Tiago, et al.
Published: (2025)

The Distribution Shift Problem in Transportation Networks using Reinforcement Learning and AI
by: Taschin, Federico, et al.
Published: (2025)

Learning-based Multi-agent Race Strategies in Formula 1
by: Fieni, Giona, et al.
Published: (2026)

KAPPS: A knowledge-based CPPS Architecture for the Circular Factory
by: Hoffmann, Etienne, et al.
Published: (2026)

Explainable AI based System for Supply Air Temperature Forecast
by: Eik, Marika, et al.
Published: (2025)

Diffusion Model-based Parameter Estimation in Dynamic Power Systems
by: Zhu, Feiqin, et al.
Published: (2024)

Learning and Optimization for Price-based Demand Response of Electric Vehicle Charging
by: Gu, Chengyang, et al.
Published: (2024)

Optimized Task Assignment and Predictive Maintenance for Industrial Machines using Markov Decision Process
by: Nasir, Ali, et al.
Published: (2024)

TSViT: A Time Series Vision Transformer for Fault Diagnosis
by: Zhang, Shouhua, et al.
Published: (2023)

End-to-End Learning-based Operation of Integrated Energy Systems for Buildings and Data Centers
by: Pu, Zhenyu, et al.
Published: (2026)

Federated Prompt-based Decision Transformer for Customized VR Services in Mobile Edge Computing System
by: Zhou, Tailin, et al.
Published: (2024)

Perimeter Control with Heterogeneous Metering Rates for Cordon Signals: A Physics-Regularized Multi-Agent Reinforcement Learning Approach
by: Yu, Jiajie, et al.
Published: (2023)

Robust Deep Reinforcement Learning for Inverter-based Volt-Var Control in Partially Observable Distribution Networks
by: Liu, Qiong, et al.
Published: (2024)