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

AI-integrated IQPD framework of quality prediction and diagnostics in small-sample multi-unit pharmaceutical manufacturing: Advancing from experience-driven to data-driven manufacturing

Wang, K., Chen, X., Li, N., Feng, H., Liu, X., Wang, Y., Wu, Y., Guo, Y., Xu, S., Yao, L., et al. (2025) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2025.06.001 · Cited by 4

Digital-twin-based AGV cluster dynamic scheduling for solar cell production workshop using deep reinforcement learning

Zhou, Z., Xu, L., Chen, Y., Liao, L., & Xu, Z. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.130772 · Cited by 4

Digital twin technology and its application in water governance: China’s practices and achievements

Peng, J. (2025) · International Journal of Water Resources Development · doi:10.1080/07900627.2025.2544810 · Cited by 4

Predicting Assembly Geometric Errors Based on Transformer Neural Networks

Wang, W., Li, H., Liu, P., Niu, B., Sun, J., & Wen, B. (2024) · Machines · doi:10.3390/machines12030161 · Cited by 5

Television shows ideation, and testing with smart digital twins to advance ratings

Hornik, J., & Rachamim, M. (2024) · Electronic Commerce Research · doi:10.1007/s10660-024-09876-9 · Cited by 6

Optimizing Batch Crystallization with Model-based Design of Experiments

Lynch, H. G., Bjarnason, A., Laky, D. J., Brown, C. J., & Dowling, A. W. (2024) · Systems and Control Transactions · doi:10.69997/sct.152239 · Cited by 4

A Dataset and a Comparison of Classification Methods for Valve Plate Fault Prediction of Piston Pump

Rojek, M., & Blachnik, M. (2024) · Applied Sciences · doi:10.3390/app14167183 · Cited by 4

Design and Implementation of an Immersive Web-Based Digital Twin Steam Turbine System for Industrial Training

Li, Z., Xiao, H. R., Wang, B., Dong, X., Shen, L., Di, X., & Du, X. (2024) · Information · doi:10.3390/info15120800 · Cited by 4

The future of 3D printing in instrumented implantable polymer meta-stents

Brosseau, C., Nocchiero, G., & Ville, J. (2025) · Annals of 3D Printed Medicine · doi:10.1016/j.stlm.2025.100211 · Cited by 4

Characterization of Optical Fibers Directly Embedded on Metal Using a Particle Spray-Based Method

Lü, X., Thomas, P. J., Zhang, Y., Liao, H., Gomes, S., & Hellevang, J. O. (2020) · IEEE Sensors Journal · doi:10.1109/jsen.2020.2977251 · Cited by 4

Mathematical modeling—Computer-aided food engineering

Erdoğdu, F., Datta, A. K., Vitrac, O., Marra, F., Verboven, P., Sarghini, F., & Nicolaï, B. M. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-821292-9.00007-8 · Cited by 4

India’s Opportunities and Challenges in Establishing a Twin Registry: An Unexplored Human Resource for the World’s Second-Most Populous Nation

Dhar, R., Rana, S., Srivastava, T. P., Nayek, A., Sharma, J. B., Kaur, D., Kalari, K. R., Singh, H., & Karmakar, S. (2022) · Twin Research and Human Genetics · doi:10.1017/thg.2022.24 · Cited by 4

Substation Digital Twin Framework Design and Key Technology Research

Guo, J., Xie, J., Mi, S., Su, D., Wang, T., Yang, Y., & Wang, S. (2022) · IEEE China International Youth Conference on Electrical Engineering (CIYCEE) · doi:10.1109/ciycee55749.2022.9958999 · Cited by 4

Digital Twin applications using the SIMULTAN data model and Python

Bühler, M., Steiner, B., & Bednar, T. (2022) · IOP Conference Series Earth and Environmental Science · doi:10.1088/1755-1315/1101/8/082015 · Cited by 4

Dynamic Fit Optimization and Effect Evaluation of a Female Wetsuit Based on Virtual Technology

Wu, X., Cheng, Z., & Kuzmichev, V. E. (2023) · Sustainability · doi:10.3390/su15032197 · Cited by 4

Digital Twins Data Visualization Methods. Problems of Human Interaction: A Review

Palazhchenko, Y., Shendryk, V., & Shendryk, S. (2023) · Lecture notes in networks and systems · doi:10.1007/978-3-031-31066-9_53 · Cited by 6

Estimating Parameters with Data Farming for Condition-Based Maintenance in a Digital Twin

Wuttke, A., Hunker, J., Rabe, M., & Diepenbrock, J.-P. (2023) · Winter Simulation Conference · doi:10.1109/wsc60868.2023.10408594 · Cited by 4

Intelligent bridge construction method driven by digital twin

Zhu, J., Zhu, Q., Bing, Z., Wang, B., & Liang, C. (2024) · National Remote Sensing Bulletin · doi:10.11834/jrs.20232590 · Cited by 4

Editorial for the special issue on Digital twin in industry

Tao, F., Liu, A., Anwer, N., Zhang, M., Wang, L., & Nee, A. Y. C. (2024) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-024-13440-y · Cited by 5

Scheme and algorithm designs for optical fiber sensors based configuration inversion of umbilical cables in deep-water

Zhou, X., Wang, S., Yu, L., Yang, Y., & Gao, L. (2025) · Ocean Engineering · doi:10.1016/j.oceaneng.2025.121363 · Cited by 3

From Passive to Proactive: A Novel Paradigm for Odor Control in Drinking Water

Ning, R., Xiang, Y., Wang, D., Zhang, K., Wei, Z., Xu, K., Gao, N., Yu, S., Li, L., & Snyder, S. A. (2025) · Environmental Science & Technology · doi:10.1021/acs.est.5c04330 · Cited by 3

Virtual Measurement of Explosion-Proof Performance: Application of an Improved RBF-GMSE-Based Surrogate Model to the Safety Performance Characterization of Coal Mine Equipment

Xue, X., Wan, H., Zhang, H., Yang, J., Wang, Y., Yang, W., & Chen, F. (2025) · Applied Sciences · doi:10.3390/app15179765 · Cited by 3

A multi-phase approach to digital-physical testing of aerospace systems

Mi, Y., Wang, X., Changwei, J., Zhang, J., Zou, X., & Shi, X. (2025) · Digital engineering. · doi:10.1016/j.dte.2025.100064 · Cited by 3

Hypermedia-based digital twin ecosystems: A proposal for digital twin interoperability

Giulianelli, A., Burattini, S., Ciortea, A., & Ricci, A. (2025) · Future Generation Computer Systems · doi:10.1016/j.future.2025.108219 · Cited by 4

Battery system integration for electric mobility

Zhao, J., Yan, H., Zheng, Y., Li, Y., Feng, X., Fowler, M. W., Ouyang, M., Burke, A. F., & Sperling, D. (2026) · Joule · doi:10.1016/j.joule.2026.102445 · Cited by 3

A knowledge graph framework for digital twins of chemical processes

Zhang, S., Zhang, J., & Lapkin, A. A. (2026) · Nature Chemical Engineering · doi:10.1038/s44286-026-00392-1 · Cited by 8

Prediction-Based Scheduling for Digital Twin Synchronization With AoI and Spatial Urgency

Kim, K., Kim, J.-W., & Lee, H.-S. (2026) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2026.3698880 · Cited by 3

Decision-grade digital twins for in situ bioremediation of contaminated soil and groundwater: a critical review

Cycoń, M. (2026) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2026.1866957 · Cited by 3

Digital twin construction for biomimetic materials

Shen, T., Zhang, C., Jiang, L., & Dong, Z. (2026) · Advanced bionics. · doi:10.1016/j.abs.2026.07.006 · Cited by 3

A Digital Twin Approach for Assembly Design of Proton Exchange Membrane Fuel Cell Stacks

Liao, S., Qiu, D., Yi, P., & Peng, L. (2023) · International Conference on Design Science (ICDS) · doi:10.1109/icds59539.2023.10311447 · Cited by 3

Quantum and AI-Enhanced Digital Twin Systems

Braga, D. M., & Rawal, B. S. (2024) · International Conference on Computing, Communication and Networking Technologies (ICCCNT) · doi:10.1109/icccnt61001.2024.10724642 · Cited by 3

Understanding pedestrian dynamics using machine learning with real-time urban sensors

Asher, M., Oswald, Y., & Malleson, N. (2025) · Environment and Planning B Urban Analytics and City Science · doi:10.1177/23998083251319058 · Cited by 3

Intelligent calibration of wind turbine gearbox dynamic model by integrating LSTM agent model and GA-PSO algorithm

Xiao, K., Zhou, J., Chen, F., Zhou, Y., Fei, X., Cao, Z., & Cui, S. (2025) · Journal of Vibration and Control · doi:10.1177/10775463251341370 · Cited by 3

Applying AI to conservation challenges

Swami, N. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-817976-5.00002-4 · Cited by 3

A blockchain-based cooperative modeling method for digital twin ontology model of the mechanical product

Zheng, M., & Tian, L. (2022) · MATEC Web of Conferences · doi:10.1051/matecconf/202235502018 · Cited by 3

Review of Pairing Exercises Involving a Real Event and its Virtual Model up to the Supervision of Complex Procedures

Razek, A. (2021) · Journal of Human Earth and Future · doi:10.28991/hef-2021-02-04-010 · Cited by 3

The Future of Blockchain

Charles, W. (2022) · Blockchain technologies · doi:10.1007/978-981-19-2976-2_14 · Cited by 4

Introduction to Computational Mathematics in Industrial Systems

Yazdi, M. (2024) · Springer series in reliability engineering · doi:10.1007/978-3-031-53514-7_1 · Cited by 3

Design and implementation of the digital twin system for the negative ion based neutral beam injection

Gu, Y., Hu, C., Zhao, Y., Li, Y., Cui, Q., & Bai, R. (2025) · Nuclear Engineering and Technology · doi:10.1016/j.net.2025.103540 · Cited by 3

A new knowledgeable encapsulation method of steel production scheduling model

Chen, X., Jiang, G., Li, G., Zuo, Y. N., & Xiang, F. (2020) · Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · doi:10.1177/0954405420944813 · Cited by 3

NECESSITY AND PROSPECTS OF “SMART CITY” TECHNOLOGY DEVELOPMENT IN UKRAINE

HUTNIK, O. O., & CHAYKA, Y. I. (2022) · Ukrainian Journal of Civil Engineering and Architecture · doi:10.30838/j.bpsacea.2312.050722.44.863 · Cited by 2

Smart Facilities Management using Digital Twin with 3D Web-Based Technology

Sinthamrongruk, T., Narongtuwapan, K., Wongkum, P., Suangswang, P., Thongphun, K., & Akarajaka, T. (2024) · Joint International Conference on Digital Arts, Media and Technology with ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering (ECTI DAMT & NCON) · doi:10.1109/ectidamtncon60518.2024.10480018 · Cited by 2

Digital Twin Concept and its Applications: A Review

Ji, T., & Nor, N. M. (2024) · Journal of Engineering Science and Technology Review · doi:10.25103/jestr.172.22 · Cited by 2

Digital tools for advancing digital enablement of business: A toolset advancing business maturity

Telukdarie, A., Sishi, M., & Tshukudu, C. (2024) · Procedia Computer Science · doi:10.1016/j.procs.2024.06.229 · Cited by 3

Contributions of Digital Twins Services to the Implementation of the Circular Economy

Aouani, S., Marangé, P., Robin, V., & Traoré, M. K. (2024) · IFIP advances in information and communication technology · doi:10.1007/978-3-031-71743-7_10 · Cited by 2

Model-based prototype design, construction and operation of closed-loop control system of solid waste treatment unit

Hu, D., Li, S., Liu, X., Liu, H., & Liu, H. (2025) · Acta Astronautica · doi:10.1016/j.actaastro.2025.01.028 · Cited by 2

Applications and challenges of digital twins of floating wind turbines

Daraki, M.-S., Mina, B., Almasoudi, M., Charalambidi, B. G., Mančić, M., Heng, J., & Baniotopoulos, C. C. (2024) · doi:10.5937/simterm24053s · Cited by 2

Unified physics-informed ResNet model for comprehensive performance prediction of finned-tube evaporators

Zhang, B., Liang, X.-Y., & Zhang, C. (2025) · International Journal of Refrigeration · doi:10.1016/j.ijrefrig.2025.03.042 · Cited by 2

Physics-informed neuromorphic learning: Enabling scalable industrial digital twins

Li, X., Chen, C., Tang, Y., Xu, Q., Xu, L., Zhang, Y., Ding, Z., & Guan, X. (2025) · National Science Open · doi:10.1360/nso/20250016 · Cited by 2

Virtual Touchability: the impact of wearable sensors in Metaverse naturalization

Far, S. B., Rad, A. I., Bamakan, S. M. H., & Zareravasan, A. (2025) · Discover Applied Sciences · doi:10.1007/s42452-025-07423-1 · Cited by 2

Support Vector Regression-based Cable Temperature Prediction for Digital Twin Applications

Zhou, X., Li, Y., Zhang, Z., Wang, X., Hu, D., & Tan, Y. (2025) · IEEE International Symposium on the Application of Artificial Intelligence in Electrical Engineering (AAIEE) · doi:10.1109/aaiee64965.2025.11101636 · Cited by 2

Research on the construction and fidelity evaluation of digital twins for CNC machine tools

Zhang, X., Chen, W., Li, J., Zhao, Z., Yin, Z., Mu, Z., & Wang, H. (2025) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-025-16580-x · Cited by 2

Comparative analysis on AI-driven human digital twin for personalized and predictive medicine

Din, G. M., Shams, M. U., Rahmani, A. N., Rehman, A., Ahmed, M. M., & Shoukat, M. A. (2025) · Journal of Clinical Practice and Medical Research · doi:10.59324/jcpmr.2025.1(1).06 · Cited by 3

Digital twin-augmented spatio-temporal Bayesian nowcasting model for emissions accounting in complex urban grid systems

Jiang, Y., Cheng, M., Pan, S., Liu, X., Geng, Z., & Gao, H. O. (2025) · Information Sciences · doi:10.1016/j.ins.2025.122918 · Cited by 2

A Digital Twin System for Collaborative Manufacturing of Robotic Swarms in Major Equipment

Tong, Y., Feng, Y., Wang, Y., & Wu, C. (2025) · Youth Academic Annual Conference of Chinese Association of Automation (YAC) · doi:10.1109/yac66630.2025.11149851 · Cited by 3

Explainable mechanism for production process anomalies based on digital twin

Qian, W., Zhang, L., Guo, Y., Geng, S., Jiang, M., Zheng, Y., Wang, S., & Huang, S. (2026) · Nature Communications · doi:10.1038/s41467-025-68281-4 · Cited by 2

A lightweight digital twin of cold metal transfer welding based on twin data and improved C-DCGAN algorithm

Li, X., Yang, K., Huang, H., Chen, J., & Yang, J. (2026) · Applied Intelligence · doi:10.1007/s10489-025-07042-8 · Cited by 2

Reservoir computing as digital twins for controlling nonlinear dynamical systems

Sun, H., Zhou, X., Cao, R., Hou, J., Guan, C., & Leng, S. (2026) · Nonlinear Dynamics · doi:10.1007/s11071-025-12087-y · Cited by 2

A Novel LLM-Assisted Approach for Automated Mechanical Design of Regularized Geometries in CAD System

Kim, S., Lee, C., & Park, J. (2026) · IEEE Access · doi:10.1109/access.2026.3666652 · Cited by 2

Review of tool condition monitoring in milling of thin-walled parts based on digital twin technology

Gao, S., Zhang, X., Yu, F., Wen, L., & Yu, T. (2026) · Journal of the Brazilian Society of Mechanical Sciences and Engineering · doi:10.1007/s40430-026-06457-9 · Cited by 2

Probabilistic Digital Twins for Transmission Pipelines

Ayello, F., Liu, G., Yang, Y., Zhang, Y., Li, L., & Zhang, S. (2021) · NACE CORROSION Conference · doi:10.5006/c2021-16780 · Cited by 2

Real-Time Data-Driven Digital Twin Workshop Web Interactive Application

Cao, H., Liu, L., Zhou, S., Li, J., Chang, Y., & Wei, W. (2022) · Lecture notes in electrical engineering · doi:10.1007/978-981-19-0572-8_13 · Cited by 2

From service to digital twin service

Qi, Q., Tao, F., & Nee, A. Y. C. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-91300-3.00006-1 · Cited by 2

Digital Twins : High Resolution Disease Models for Optimized Diagnosis and Treatment

Lilja, S. (2022) · Linköping University medical dissertations · doi:10.3384/9789179292157 · Cited by 1

Dynamic monitoring system of prefabricated component production line based on digital twin

Liu, X., Jiang, R., Xingkai, W. E. I., Zhang, G., Linqian, T. I. A. N., Lingzi, W. A. N. G., & Zheng, X. (2022) · International Conference on Smart Transportation and City Engineering (STCE) · doi:10.1117/12.2658288 · Cited by 2

Der digitale Zwilling für die perioperative Medizin – ein spannender Blick in die Zukunft klinischer Forschung

Niklas, C., Hölle, T., Dugas, M., Weigand, M. A., & Larmann, J. (2023) · Die Anaesthesiologie · doi:10.1007/s00101-023-01251-x · Cited by 2

Climate Smart Farming – Deployment of Digital Twin Concepts in Agricultural Seed Value Chain

Vadlamani, R., Chevala, V. N., & Mittal, P. (2023) · International Conference on Industrial Engineering and Operations Management (IEOM) · doi:10.46254/an12.20220049 · Cited by 2

EVALUATION OF MODEL BIAS IDENTIFICATION APPROACHES BASED ON BAYESIAN INFERENCE AND APPLICATIONS TO DIGITAL TWINS

Arcones, D. A., Weiser, M., Koutsourelakis, F.-S., & Unger, J. F. (2023) · UNCECOMP Proceedings · doi:10.7712/120223.10325.19795 · Cited by 2

The Evolution of Manufacturing: A Comprehensive Analysis of Industry 4.0 and Its Frameworks

Madakam, S., Revulagadda, R. K., Mishra, V., & Kundu, K. (2023) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-83753-060-120231019 · Cited by 2

Leveraging epoch‐era analysis and digital twin for effective system concept and execution: A CO2$_2$ storage salt‐cave project

Vieira, D. P., Fonseca, Í. A., Nishimoto, K., Assi, G. R. S., Gaspar, H. M., & Rhodes, D. H. (2023) · Systems Engineering · doi:10.1002/sys.21741 · Cited by 2

The Degree of Entanglement: Cyber-Physical Awareness in Digital Twin Applications

Picone, M., Mariani, S., Cavicchioli, R., Burgio, P., & Cherif, A. H. (2024) · IEEE Consumer Communications and Networking Conference · doi:10.1109/ccnc51664.2024.10454629 · Cited by 2

Digital Twin-Driven Smart Transportation Infrastructure: Connotation, Reference Model, Applications and Research Issues

Wang, Y., Chen, Z., Zhang, C., Hu, H., Zhang, Z., & Zhu, M. (2024) · IEEE International Conference on Industrial Technology (ICIT) · doi:10.1109/icit58233.2024.10540741 · Cited by 2

Designing Interactive Virtual Tours for Education: Two Case Studies on Virtual Tours of the Chemistry and Biochemistry Laboratories

Chen, M., Elliott, D., Dempski, R. E., & Picón, R. O. (2024) · International Conference on the Foundations of Digital Games (FDG) · doi:10.1145/3649921.3656982 · Cited by 2

Fluidware Meets Digital Twins

Casadei, R., Fornari, F., Mariani, S., & Savaglio, C. (2024) · Internet of things · doi:10.1007/978-3-031-62146-8_7 · Cited by 2

Security of Metrology in the Digital Age

Abouhogail, R. A. (2025) · Practice, progress, and proficiency in sustainability · doi:10.4018/979-8-3693-7117-6.ch004 · Cited by 2

State of Electrical Metrology and Possible Advancements Utilizing Extended Reality

Mageed, H. M. A., Azzam, I., & Breidi, F. (2025) · MAPAN · doi:10.1007/s12647-024-00795-6 · Cited by 2

DTL-GNN: Digital Twin Lightweight Method Based on Graph Neural Network

Li, C., Yao, L., Lu, Y., Zhang, S., & Zhang, T. (2025) · Future Internet · doi:10.3390/fi17020065 · Cited by 3

Digital Twin Assistant Active Design and Optimization of Steel Mega-Sub Controlled Structural System under Severe Earthquake Waves

Wei, Z., Zhang, X., Sun, F., & Wang, W. Y. (2022) · Materials · doi:10.3390/ma15186382 · Cited by 2

A novel bionic decision-making mechanism for digital twin-based manufacturing system

Liu, S., Zheng, P., & Shang, S. (2023) · Manufacturing Letters · doi:10.1016/j.mfglet.2023.08.119 · Cited by 2

Simplifying the Process of Going From Cells to Tissues Using Statistical Mechanics

Hussan, J. R., Trew, M. L., & Hunter, P. J. (2022) · Frontiers in Physiology · doi:10.3389/fphys.2022.837027 · Cited by 3

Digital twins of nonlinear dynamical systemsPreprint

Kong, L.-W., Weng, Y., Glaz, B. J., Haile, M., & Lai, Y. (2022) · Research Square · doi:10.21203/rs.3.rs-1871210/v1 · Cited by 2

Using digital twin in product design and development

Zhong, R. Y., Su, S., & Yu, C. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-28993-4.00040-8 · Cited by 2

HWoDT Framework: A toolchain to build interoperable Digital Twin Ecosystems

Giulianelli, A., Burattini, S., Ciortea, A., & Ricci, A. (2025) · SoftwareX · doi:10.1016/j.softx.2025.102275 · Cited by 2

Production process management for intelligent coal mining based on digital twin

Zhang, X., Lv, X., Wang, Y., & Fan, H. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-91300-3.00008-5 · Cited by 1

Digital twin enhanced tribo-test service

Zhang, Z., Ma, Y., He, K., Hu, R., & Hu, M. (2022) · Elsevier eBooks · doi:10.1016/b978-0-323-91300-3.00009-7 · Cited by 1

Digital twin prevalence in the medical caring fields: A bibliomatrics study and visualization analysis through CiteSpace

Gong, P., Chen, X., Zhou, T., Tian, Y., & Su, M. (2024) · Interdisciplinary Nursing Research · doi:10.1097/nr9.0000000000000062 · Cited by 1

Modeling of Digital Twins

Gupta, S., Iyer, R. S., & Kumar, S. (2024) · Springer eBooks · doi:10.1007/978-3-031-76564-3_5 · Cited by 1

Gemelos digitales pulmonares

Tena, A. F., Arnedo, C., Houzeaux, G., & Eguzkitza, B. (2024) · Open Respiratory Archives · doi:10.1016/j.opresp.2024.100394 · Cited by 1

Integration of digital twin and blockchain for smart hospitals

Hassani, H., & MacFeely, S. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-36370-2.00030-x · Cited by 3

Study and Design of the Digital Twin System for the Intelligent Ship Energy Efficiency

Jing, Z., Wang, K., Cong, L., Wang, Z., Meng, W., & Huang, L. (2025) · Lecture notes in electrical engineering · doi:10.1007/978-981-96-3965-6_30 · Cited by 1

Analyzing potential collaboration methods for digital twin teams developed on heterogeneous blockchains without a central authority

Far, S. B., & Bamakan, S. M. H. (2025) · Advanced Engineering Informatics · doi:10.1016/j.aei.2025.103616 · Cited by 1

Impact of flow history and local geometry on heat transfer in the supersonic channel

Malastowski, N. S., Kiselev, N. A., Zditovets, A. G., & Vinogradov, Y. A. (2025) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2025.127529 · Cited by 1

Research on the Construction Process of Digital Twin Maturity Evaluation Model

Li, Y., Wang, F., Chen, Q., Su, M., & Xiang, P. (2025) · Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence (DEAI) · doi:10.1145/3745238.3745280 · Cited by 1

Machine Learning-Based Prediction Model in Digital Twin System of Wind Farm

Yang, H., Jiao, Y., Wang, X., & Luo, X. (2025) · Chinese Control and Decision Conference (CCDC) · doi:10.1109/ccdc65474.2025.11090170 · Cited by 1

Towards Intelligent Monitoring and Control of Industrial Internet of Things Deployments with Causality-Aware Digital Twins

Mariani, S., Martinelli, M., Morandi, R., Barbone, A., & Picone, M. (2025) · International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT) · doi:10.1109/dcoss-iot65416.2025.00089 · Cited by 1

Digital twin-driven decision support approach of production process for smart manufacturing

Yin, L., Zhang, L., Zhang, Y., & Xie, F. (2025) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-025-16363-4 · Cited by 3

Versatile reservoir computing for heterogeneous complex networks

Du, Y., Fan, H., & Wang, X. (2025) · Physical Review Applied · doi:10.1103/vb8m-b151 · Cited by 1

TransPhyX: A data-driven method for dynamic physical field prediction in stochastic load time-series

Lin, Q., Gu, F., Qiu, M., Wang, C., Zhuang, J., & Hong, J. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.114492 · Cited by 1

A survey of digital twin implementations for industrial transformation: analysis of real-world case studies

Bahfir, S., Belkorchi, W., & Zemmouchi-Ghomari, L. (2025) · Australian Journal of Multi-Disciplinary Engineering · doi:10.1080/14488388.2025.2565021 · Cited by 1

Toward Digital and Intelligent Ship Energy Management System: Guarantee secure, economic, green sailing.

Teng, F., Zhang, Y., Liu, H., Li, Y., Li, T., Pedersen, T. B., & Gao, W. (2025) · IEEE Electrification Magazine · doi:10.1109/mele.2025.3588462 · Cited by 1

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

Malik, A. A. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2104.03034 · Cited by 3

Digital twin modeling features for smart manufacturing

Nafikov, A. M., & Стучилин, В. В. (2026) · Automation Modern Techologies · doi:10.36652/0869-4931-2026-80-1-29-34

Special issue on digital twins and simulation in smart manufacturing

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