Make more digital twins

Smart manufacturing must embrace big data

Kusiak, A. (2017) · Nature · doi:10.1038/544023a · Cited by 636

Digital Twin Driven Smart Manufacturing

Tao, F., Zhang, M., & Nee, A. Y. C. (2019) · Elsevier eBooks · doi:10.1016/c2018-0-02206-9 · Cited by 284

Enhancing Construction Management Digital Twins Through Process Mining of Progress Logs

Wang, Y., Liao, S., Gong, Z., Deng, F., & Yin, S.-Y. (2024) · Sustainability · doi:10.3390/su162210064 · Cited by 13

Six-dimensional digital twin modeling and software platform design for complex industrial systems

Li, N., Xie, G., Zhang, X., Shi, H., Nie, X., Wang, Y., Wang, J.-A., & Wang, J. (2025) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-025-02567-8 · Cited by 10

Distributing intelligent functionalities in the Internet of Things with agents and Digital Twins

Burattini, S., Mariani, S., Montagna, S., Picone, M., & Ricci, A. (2025) · Internet of Things · doi:10.1016/j.iot.2025.101560 · Cited by 9

Digital-Twin-Based Modeling and Fault Prediction Method for Industrial Robots

Wang, Q., Yang, H., Zhang, H., Lu, J., Zhang, Y., Xiao, G., & Cheok, A. D. (2025) · IEEE Journal of Emerging and Selected Topics in Industrial Electronics · doi:10.1109/jestie.2025.3565106 · Cited by 9

A digital twin shop-floor construction method towards seamless and resilient control

Zhang, C., Tao, F., Liu, W., Cheng, Y., & Wang, L. (2025) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2025.07.017 · Cited by 9

The next-generation digital twin: from advanced sensing towards artificial intelligence-assisted physical-virtual system

Zhu, J., Yang, Y., Xi, M., Ji, S., Jia, L., & Hu, T. (2025) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2025.100942 · Cited by 10

Digital twin applications and case studies in modern power grid management

Subramanian, N., & Stonier, A. A. (2026) · Energy Reports · doi:10.1016/j.egyr.2026.109218 · Cited by 11

Harnessing the potential of digital twins in seismology

Zilio, L. D., Giardini, D., Carbonell, R., & Wiemer, S. (2023) · Nature Reviews Earth & Environment · doi:10.1038/s43017-023-00469-y · Cited by 9

Visualization and Analysis of Research Areas and Hot Topics in the Field of Digital Twins

Gao, L., Li, S., & Guo, H. (2024) · IEEE Access · doi:10.1109/access.2024.3365291 · Cited by 10

An adaptive evolutionary framework for the decision-making models of digital twin machining system

Liu, S., Shen, H., Li, J., Lu, Y., & Bao, J. (2021) · IEEE International Conference on Automation Science and Engineering (CASE) · doi:10.1109/case49439.2021.9551595 · Cited by 9

The Virtual Geographic Environments: More than the Digital Twin of the Physical Geographical Environments

Lin, H., Xu, B., Chen, Y., Qi, J., & You, L. (2022) · Springer eBooks · doi:10.1007/978-981-19-3816-0_3 · Cited by 9

High-accuracy virtual testing of air conditioner’s digital twin focusing on key material’s deformation and fracture behavior prediction

Fu, S., Wan, Z., Lü, W., Liu, H., Zhang, P., Yu, B., Tan, M. J., Pan, F., & Liu, Z. (2022) · Scientific Reports · doi:10.1038/s41598-022-16511-w · Cited by 9

Digital Twins and Blockchain for IoT Management

Samaniego, M., & Deters, R. (2023) · ACM International Symposium on Blockchain and Secure Critical Infrastructure (BSCI) · doi:10.1145/3594556.3594611 · Cited by 12

How the map becomes the territory: prediction, performativity and the process of taking digital twins for granted

Leonardi, P. M., & Leavell, V. (2024) · Journal of Organization Design · doi:10.1007/s41469-024-00164-2 · Cited by 10

Take five: about the beat and the bar of annual and 5-year periodic national forest inventories

Bontemps, J., & Bouriaud, O. (2024) · Annals of Forest Science · doi:10.1186/s13595-024-01268-1 · Cited by 8

Research on the Digital Twin System of Welding Robots Driven by Data

Wang, S., Jiao, Y., Wang, L., Wang, W., Ma, X., Xu, Q., & Lu, J. (2025) · Sensors · doi:10.3390/s25133889 · Cited by 8

Object-oriented modeling mechanism for digital twin workshop elements

Liu, X., Feng, F., Ye, D., Hu, T., Wang, C., Tao, F., & Hai, Y. (2025) · Advanced Engineering Informatics · doi:10.1016/j.aei.2025.103635 · Cited by 9

A review on machine learning-based prognostics and health management for hydrogen fuel cells

Meng, H., Liang, J., Hu, M., Salehi, F., & Han, T. (2025) · Journal of Loss Prevention in the Process Industries · doi:10.1016/j.jlp.2025.105833 · Cited by 9

Towards the Development of Societal Twins

Birks, D., Heppenstall, A. J., & Malleson, N. (2020) · Frontiers in artificial intelligence and applications · doi:10.3233/faia200435 · Cited by 8

Decarbonising Transport with Intelligent Mobility

Bishop, J. D. K. (2022) · Lecture notes in energy · doi:10.1007/978-3-030-86215-2_18 · Cited by 8

Machine Learning and Digital Twin-Based Path Planning for AGVs at Automated Container Terminals

Gao, Y., Chen, C., Chang, D., Chen, S., & Song, X. T. (2022) · Advances in transdisciplinary engineering · doi:10.3233/atde220672 · Cited by 8

Fine-grained decomposition of complex digital twin systems driven by semantic-topological-dynamic associations

Wen, X., Sun, Y., Liu, S., Bao, J., & Zhang, D. (2024) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2024.10.023 · Cited by 8

Digital Twin‐Enabled Online Battlefield Learning with Random Finite Sets

Wang, P., Yang, M., Zhu, J., Peng, Y. J., & Li, G. (2021) · Computational Intelligence and Neuroscience · doi:10.1155/2021/5582241 · Cited by 8

Modeling an Industrial Revolution: How to Manage Large-Scale, Complex IoT Ecosystems?

Kulcsár, G., Varga, P., Tatara, M. S., Montori, F., Inigo, M. A., Urgese, G., & Azzoni, P. (2021) · Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) · Cited by 8

High-Fidelity Digital Twin Modeling Method for Contactor Operation Simulation

Zhang, B., Zhang, M., & Dong, T. (2021) · International Symposium on Linear Drives for Industry Applications (LDIA) · doi:10.1109/ldia49489.2021.9505888 · Cited by 8

A Bayesian Framework for Simulation‐based Digital Twins of Bridges

Arcones, D. A., Weiser, M., Koutsourelakis, P., & Unger, J. F. (2023) · ce/papers · doi:10.1002/cepa.2177 · Cited by 8

A Parallel Logistic Network Simulation Method and System to Improve Logistics Efficiency

Liu, S., Zhuang, X., Yan, L., Wang, Y., Wu, S., Lv, Y.-S., Zhu, F.-H., & Wang, F.-Y. (2024) · IEEE Journal of Radio Frequency Identification · doi:10.1109/jrfid.2024.3392943 · Cited by 7

Towards Trusted and Intelligent Cyber-Physical Systems: A Security-by-Design ApproachPreprint

Suhail, S. (2021) · doi:10.36227/techrxiv.16836814.v1 · Cited by 8

Developing physics-informed filters to align unattributed fragmental manufacturing data against a digital characteristics space (DCS)

Liu, H., Wu, V. L., Weill, M., Li, S., Yang, X. Z., Politis, D. J., & Wang, L. (2024) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2024.09.002 · Cited by 7

Construction of a Digital Twin System and Dynamic Scheduling Simulation Analysis of a Flexible Assembly Workshops with Island Layout

Liu, J., Zhang, D., Liu, Z.-P., Guo, T., & Yan, Y. (2024) · Sustainability · doi:10.3390/su16208851 · Cited by 7

Development of a boundary-driven FEM-SMU framework for enhanced stiffened plate performance prediction of ship structures as an essential part for digital twin

Wang, Z., Kong, X., & Wu, W. (2025) · Ocean Engineering · doi:10.1016/j.oceaneng.2025.121159 · Cited by 7

Harnessing AI and Quantum Computing for Revolutionizing Drug Discovery and Approval Processes: Case Example for Collagen Toxicity

Braga, D. M., & Rawal, B. (2025) · JMIR Bioinformatics and Biotechnology · doi:10.2196/69800 · Cited by 7

A GIS-portal platform from the data perspective to energy hub digitalization solutions- A review and a case study

Nezhad, M. M., Moradian, S., Guezgouz, M., Shi, X., Avelin, A., & Wallin, F. (2025) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2025.116019 · Cited by 14

Robotic disassembly sequence dynamic planning under uncertain irremovable condition using dueling deep Q-network based on digital twin

Liu, J., Xu, Z., Xu, W., Qi, L., Han, Y., & Zhou, Z. (2025) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2025.103132 · Cited by 7

Opportunities and challenges in the application of Digital Twins for orchard management

Liu, X., He, L., Niu, S., Li, R., Majeed, Y., Sun, X., Chen, J., Li, X., Walsh, K. B., & Fu, L. (2025) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2025.111104 · Cited by 7

Detecting failure of a material handling system through a cognitive twin

D’Amico, R. D., Sarkar, A., Karray, M. H., Addepalli, S., & Erkoyuncu, J. A. (2022) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2022.10.128 · Cited by 7

Üretim Planlama ve Kontrol Süreçlerinde Dijital İkiz Teknolojisinin Kullanılması: Tekstil Sektöründe Bir Uygulama

KOÇAK, A., & Yıldız, A. (2022) · Gazi Üniversitesi Fen Bilimleri Dergisi Part C Tasarım ve Teknoloji · doi:10.29109/gujsc.1170021 · Cited by 7

Digital twin models of replicative ground stones: insight into simulating usage of Upper Paleolithic tools

Marulli, M. R., Sorrentino, G., Menna, F., & Paggi, M. (2023) · Scientific Reports · doi:10.1038/s41598-023-45425-4 · Cited by 7

A fast scene geometric modeling approach for digital twins combining neural rendering and model retrieval

Sun, Z., Zheng, H., Lv, C., & Bao, J. (2024) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2024.2350539 · Cited by 7

A digital twin-driven human-machine interactive assembly method based on lightweight multi-target detection and assembly feature generation

Cheng, D., Hu, B., Feng, Y., Yang, J., Wang, B., Gong, H., & Tan, J. (2024) · International Journal of Production Research · doi:10.1080/00207543.2024.2354853 · Cited by 7

Digital Twin Continuum: a Key Enabler for Pervasive Cyber-Physical Environments

Barbone, A., Burattini, S., Martinelli, M., Picone, M., Ricci, A., & Virdis, A. (2024) · International Conference on Computer Communications and Networks (ICCCN) · doi:10.1109/icccn61486.2024.10637565 · Cited by 7

Towards LLM-Enhanced Digital Twins of Intelligent Computing Center

Yang, Y., Liu, M., Jia, K., Dong, W., & Wang, J. Z. (2024) · IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C) · doi:10.1109/qrs-c63300.2024.00021 · Cited by 7

Digital Twins an Enabler of Digitalization in Supply Chain

Bargavi, R., & Mathivathanan, D. (2023) · Environmental footprints and eco-design of products and processes · doi:10.1007/978-981-99-4894-9_11 · Cited by 8

Inaugural Editorial - Digital Twin

Tao, F., Qi, Q., & Liu, A. (2021) · Digital Twin · doi:10.12688/digitaltwin.17471.1 · Cited by 7

Digital twin phases and futures

Grieves, M. W. (2025) · Digital engineering. · doi:10.1016/j.dte.2025.100053 · Cited by 7

Data technologies and analytics for policy and governance: a landscape review

Asensio, O. I., Moore, C. E., Ulibarrí, N., Simsekler, M. C. E., Lan, T., & Rivero, G. (2025) · Data & Policy · doi:10.1017/dap.2024.49 · Cited by 9

Digital twin-enabled cardiovascular stent optimization: a virtual reality-driven approach to mitigate angioplasty-related deformations

Wang, J., Zhang, Y., Yang, Y., Wen, X., Xing, X., Zhang, Z., & Dong, C. (2025) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-025-03352-8 · Cited by 6

Towards an open soil-plant digital twin based on STEMMUS-SCOPE model following open science

Zeng, Y., Alidoost, F., Schilperoort, B., Liu, Y., Verhoeven, S., Grootes, M. W., Wang, Y., Song, Z., Yu, D., Tang, E., et al. (2025) · Computers & Geosciences · doi:10.1016/j.cageo.2025.106013 · Cited by 6

The role of digital twin capabilities in digital service innovation deployment: a multiple case study approach

Galera‐Zarco, C., & Moretti, N. (2025) · Journal of Enterprise Information Management · doi:10.1108/jeim-05-2024-0217 · Cited by 8

The role of digital twin technology in enhancing sustainable aviation transition: A state-of-the-art review and future direction

Adu-Gyamfi, B. A. (2025) · Journal of Open Innovation Technology Market and Complexity · doi:10.1016/j.joitmc.2025.100693 · Cited by 10

Risk assessment for modern industry

Pinciroli, L., Hosseini, S. A., Chen, M., Mesa, M. V. C., Coscia, T. M., Futalef, J.-P., Marchetti, S., Miqueles, L., Menza, S. T., & Zio, E. (2025) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2025.112126 · Cited by 8

Robust subspace tracking in intelligent fault diagnosis of digital twin gas turbines base on the adaptive Markov transfer

Wang, R., Hu, J., Xin, D., Liu, S., & Zhao, K. (2025) · Applied Energy · doi:10.1016/j.apenergy.2025.126747 · Cited by 6

Collaborative digital twin ecosystems

Kuruppuarachchi, P. M., Rea, S., Wenning, B.-L., & McGibney, A. (2026) · Future Generation Computer Systems · doi:10.1016/j.future.2026.108429 · Cited by 6

Digital twin for in – space manufacturing: a comprehensive review from framework to future

Wang, L., Jiang, Y., Zhu, J., Lin, K., Ma, X., He, J., & Lu, B. (2026) · Virtual and Physical Prototyping · doi:10.1080/17452759.2026.2639147 · Cited by 6

A New General Framework for Response Prediction of Composite Structures Based on Digital Twin with Three Effective Error Correction Strategies

Zuo, J., Zhou, L. H., Qiao, L., Ding, X., Wu, Q., He, X., & Peng, X. (2023) · Applied Composite Materials · doi:10.1007/s10443-022-10096-3 · Cited by 6

Acute on chronic liver failure: prognostic models and artificial intelligence applications

Gary, P. J., Lal, A., Simonetto, D. A., Gajic, O., & de Moraes, A. G. (2023) · Hepatology Communications · doi:10.1097/hc9.0000000000000095 · Cited by 6

A modeling method of digital twin connection model based on virtual sensor

Wang, C., Liu, X., Feng, F., Sun, Y., Yuan, G., Hai, Y., & Ding, Y. S. (2025) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-025-02639-9 · Cited by 6

Digital Twins Development of Automatic Storage and Retrieval Station in a Production Line and an Integrated Robotic Manipulator

Serik, A., Zhetpissov, Y., Mosadeghzad, M., & Alizadeh, T. (2022) · Lecture notes in networks and systems · doi:10.1007/978-3-030-97672-9_19 · Cited by 6

Real-time detection method for welding parts completeness based on improved YOLOX in a digital twin environment

Li, H., Yan, X., Zhang, Y., Liu, G., Zhai, Z., Wang, X., Wang, H., Wen, X., Liu, Y., Zhang, G., et al. (2023) · Measurement Science and Technology · doi:10.1088/1361-6501/acb0ee · Cited by 6

A Digital Twin Based Approach in Healthcare

Iliuţă, M.-E., Pop, E., Moisescu, M. A., Caramihai, S. I., & Țigănoaia, B. (2023) · International Conference on Control Systems and Computer Science · doi:10.1109/cscs59211.2023.00063 · Cited by 6

Validation of a Hospital Digital Twin with Machine Learning

Ahmad, M. A., Chickarmane, V. S., Pour, F. S. A., Shariari, N., & Roy, T. D. (2023) · IEEE International Conference on Healthcare Informatics (ICHI) · doi:10.1109/ichi57859.2023.00068 · Cited by 7

Application of a Digital Twin Model in the Packaging Process of the Panel Furniture Industry

Wang, G., Xiong, X., Ying, M., & Xu, X. (2024) · Forest Products Journal · doi:10.13073/fpj-d-24-00001 · Cited by 6

Information-Based Model Discrimination for Digital Twin Behavioral Matching

Viola, J., Chen, Y., & Wang, J. (2020) · International Conference on Industrial Artificial Intelligence (IAI) · doi:10.1109/iai50351.2020.9262239 · Cited by 6

Concepts of multi-level dynamical modelling: understanding mechanisms of squamous cell carcinoma development in Fanconi anemia

Velleuer, E., Domínguez‐Hüttinger, E., Rodríguez, A., Harris, L. A., & Carlberg, C. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1254966 · Cited by 7

Some new trends of intelligent simulation optimization and scheduling in intelligent manufacturing

Li, X., & Zhang, C. (2020) · Service Oriented Computing and Applications · doi:10.1007/s11761-020-00299-6 · Cited by 6

Digital Twins of the Earth

Nativi, S., & Craglia, M. (2021) · Encyclopedia of earth sciences series/Encyclopedia of earth sciences · doi:10.1007/978-3-030-26050-7_457-1 · Cited by 6

Digital twins on trial: Can they actually solve wicked societal problems and change the world for better?

Malleson, N., Franklin, R. S., Arribas‐Bel, D., Cheng, T., & Birkin, M. H. (2024) · Environment and Planning B Urban Analytics and City Science · doi:10.1177/23998083241262893 · Cited by 6

Research on the Construction of Automobile Wheel Hub Intelligent Production Line Based on Digital Twin

Chen, Y., Zhou, M., Zhang, M., & Zha, M. (2025) · Applied Sciences · doi:10.3390/app15115871 · Cited by 5

Physics Informed Digital Twin for RIS-Assisted Wireless Communication System

Han, Q., Zhang, H., Li, Y., Yuan, D., & Ma, X. (2025) · IEEE Wireless Communications · doi:10.1109/mwc.003.2400418 · Cited by 5

A time-varying contact dynamic modeling method of kinematic pairs based on digital twin

Chen, Y., Zhang, F., & Yang, G. (2025) · Measurement · doi:10.1016/j.measurement.2025.118219 · Cited by 5

Real-time AGV cluster scheduling using attention-enhanced PPO and strategy transfer in large-scale solar cell production workshops with multiple concurrent tasks

Zhou, Z., Xu, L., Chen, Y., Liao, L., Shang, G., & Xu, Z. (2025) · International Journal of Production Research · doi:10.1080/00207543.2025.2555532 · Cited by 5

A socio-technical framework for urban digital twins: Tehran in a global comparison

Shariatpour, F., Behzadfar, M., & Jalilisadrabad, S. (2025) · Sustainable Cities and Society · doi:10.1016/j.scs.2025.106905 · Cited by 5

Sensorless wet clutch pressure control method for high-power tractors using physical and digital twins

Zhang, Y., Wang, D., Du, Y., Wen, C., Wang, L., & Wu, Z. (2025) · Biosystems Engineering · doi:10.1016/j.biosystemseng.2025.104322 · Cited by 5

Multi-agent systems for digital twin shop-floor resilient control

Zhang, C., Tao, F., Ma, X., & Cheng, Y. (2025) · Chinese Journal of Mechanical Engineering · doi:10.1016/j.cjme.2025.100206 · Cited by 5

Digital twin enabling net-zero energy building integrated grid digital transformation

Hannan, M. A., Arsad, A. Z., Jang, G., Ker, P. J., Al-Shetwi, A. Q., Begum, R. A., & Mahlia, T. M. I. (2026) · Energy Strategy Reviews · doi:10.1016/j.esr.2026.102148 · Cited by 5

M2OSS: A systematic research perspective on robotic machining errors

Zhang, T., Yang, Z., Peng, F., Tang, X., Xiao, L., Yan, R., & Huang, H. (2026) · Robotics and Computer-Integrated Manufacturing · doi:10.1016/j.rcim.2026.103298 · Cited by 5

Digital Twin Modeling of a Five-Axis Linkage Crossbeam Mobile Gantry Milling Machine

Wu, C., Tao, T., Wang, Q., Wang, L., Zhao, P., & Zhang, Y. (2023) · Advances in transdisciplinary engineering · doi:10.3233/atde230136 · Cited by 5

Cascading failure tolerance of manufacturing services collaboration network toward industrial internet platforms

Li, P., Cheng, Y., Zhang, Y., Cheng, C., & Tao, F. (2025) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-025-15056-2 · Cited by 5

The virtual-real interaction system design and interaction characteristics research of an ankle rehabilitation robot based on digital twin

Xie, S., Zhan, M., Li, Y., & Xi, F. (2025) · Technology and Health Care · doi:10.1177/09287329251337237 · Cited by 5

Leveraging real-time digital twins for smart livestreaming platforms to enhance consumers’ experience

Hornik, J., Rachamim, M., & Ofir, C. (2025) · The Journal of Supercomputing · doi:10.1007/s11227-025-07386-5 · Cited by 7

Digital twin-driven robotic arm operation simulation and health management research

Li, G., Yang, K., Dong, Z., Ji, X., & Wu, S. (2023) · Advances in Complex Systems · doi:10.1142/s1793962323410337 · Cited by 5

Mirror world: creating digital twins of the space and persons from video streamings

Jiang, L. L., Cai, L., Wu, W., & Zhou, Z. (2023) · The Visual Computer · doi:10.1007/s00371-023-03193-2 · Cited by 5

Smart sensors and IoT applied in Digital Twin for Industry 4.0

Boltaboyeva, A., Baigarayeva, Z., Postolache, O. A., Мансурова, М., Karymsakova, N., & Belgibaev, B. (2024) · International Symposium on Sensing and Instrumentation in 5G and IoT Era (ISSI) · doi:10.1109/issi63632.2024.10720505 · Cited by 5

Hydrodynamic model-driven evolutionary algorithm-based operation optimization of an experimental drainage pumping station

Li, X., Xue, S., Hou, J., Guo, Y., Liu, Y., Ma, H., Zhang, T., & Wang, S. (2024) · Journal of Water and Climate Change · doi:10.2166/wcc.2024.405 · Cited by 5

Autonomous Cooking with Digital Twin Methodology

Kannapinn, M., & Schäfer, M. (2021) · WCCM-ECCOMAS Congress · doi:10.23967/wccm-eccomas.2020.074 · Cited by 5

VR/AR/MR in the Electricity Industry: Concepts, Techniques, and Applications

Xiao, J., Yang, Q., Du, W., Wang, Y., Jiang, Y., & Liu, Y. (2023) · IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW) · doi:10.1109/vrw58643.2023.00022 · Cited by 5

Intelligent fault diagnosis method using small fault samples driven by digital data and feature enhancement

Xia, J., Huang, R., Chen, Z., Li, J., & Li, W. (2023) · Scientia Sinica Technologica · doi:10.1360/sst-2023-0018 · Cited by 5

How to Enrich Metaverse? Blockchains, AI, and Digital Twin

Li, J., Cai, S., Yang, Q., & Huang, H. (2023) · Springer eBooks · doi:10.1007/978-981-99-3648-9_2 · Cited by 5

Digital Twin Enabled Smart Control Engineering as an Industrial AI: A New Framework and A Case StudyPreprint

Viola, J., & Chen, Y. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2007.03677 · Cited by 5

Robopheus: A Virtual-Physical Interactive Mobile Robotic TestbedPreprint

Ding, X., Wang, H., Li, H., Jiang, H. T., & He, J. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2103.04391 · Cited by 5

Towards Trusted and Intelligent Cyber-Physical Systems: A Security-by-Design ApproachPreprint

Suhail, S. (2021) · doi:10.36227/techrxiv.16836814 · Cited by 5

Quality monitoring of resistance spot welding based on digital twinPreprint

Dong, J., Hu, J., & Luo, Z. (2023) · Research Square · doi:10.21203/rs.3.rs-2428723/v1 · Cited by 5

Tracking Soil Health: Monitoring and Modeling the Soil-Plant SystemPreprint

Zeng, Y., Verhoef, A., Vereecken, H., Ben‐Dor, E., Veldkamp, A., Shaw, L. J., Wang, Y., & Su, Z. (2024) · doi:10.22541/essoar.171804479.91646868/v1 · Cited by 5

Model Bias Identification for Bayesian Calibration of Stochastic Digital Twins of Bridges

Arcones, D. A., Weiser, M., Koutsourelakis, P., & Unger, J. F. (2024) · Applied Stochastic Models in Business and Industry · doi:10.1002/asmb.2897 · Cited by 4

Digitizing Dignity: Analyzing Digital Twins Through the Lens of Multidimensional Human Dignity

Barnhart, A. J. (2025) · Bioethics · doi:10.1111/bioe.70045 · Cited by 4

Flow field configurations in PEMFCs: Design, Modeling, and performance insights

Rimon, S. T. A., Shajid, S. R., Mourshed, M., & Tushar, M. S. H. K. (2025) · Energy Conversion and Management X · doi:10.1016/j.ecmx.2025.101263 · Cited by 4

Digital twin system for deepwater well construction: Enhancing operational efficiency and safety

Xu, D., Yang, J., Zheng, H., Chen, B., Yan, D., Fan, J., Tang, Q., & Zhou, Y. (2026) · Ocean Engineering · doi:10.1016/j.oceaneng.2026.124378 · Cited by 4

Artificial intelligence in modern mechatronic systems: technologies, applications, and future research directions

al Ghazo, A. T., & Salah, M. (2026) · Systems Science & Control Engineering · doi:10.1080/21642583.2026.2640267 · Cited by 4

Matrix-structured manufacturing systems: literature review and future directions

Li, W., Liu, X., Du, X., Shao, H., Zhu, T., Yang, S., & Yang, X. (2026) · International Journal of Production Research · doi:10.1080/00207543.2026.2669883 · Cited by 4

A Digital Twin System for Adaptive Aligning of Large Cylindrical Components

Fan, W. H., Xiao, R., Zhang, J., Zheng, L., & Zhou, J. H. (2024) · Applied Sciences · doi:10.3390/app14188307 · Cited by 4

Demonstration and evaluation of a digital twin-based virtual factory

Yildiz, E., Møller, C., & Bilberg, A. (2021) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-021-06825-w · Cited by 78

From Static Models to Control-Oriented Digital Twins: Towards Virtual Learning Factories for Manufacturing Innovation

Nezzi, C., Colsman, C., Rammo, J.-P., Wergmann, M., Rauch, E., & Reuter, C. (2026) · International Conference on Control, Decision and Information Technologies (CoDIT) · doi:10.1109/codit70676.2026.11631145

Framework to model virtual factories: a digital twin viewPreprint

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