The DOI matches its Crossref record; 31 of the 32 references it cites were found in a registry or an index.
Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Grieves and Vickers [35] have identified two subtypes of DT, namely: Digital Twin Prototype (DTP) and Digital Twin Instance (DTI).”
From Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0 (2025) · cites this paper as [35]
In the citing paper
“predictive maintenance [35]”
From Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0 (2025) · cites this paper as [35]
In the citing paper
“The authors of [35] proposed the term”
From Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0 (2025) · cites this paper as [35]
In the citing paper
“After the completion of a physical system, data obtained from the physical spaces is sent to the virtual space and reciprocally, used to oversee and anticipate the system's performance [35].”
From Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0 (2025) · cites this paper as [35]
In the citing paper
“A Digital Twin consists of three primary components: the physical system, the virtual system, and the service system, along with Digital Twin Data that continuously connect these elements [4,100].”
From Analysis of Digital Twin Applications in Energy Efficiency: A Systematic Review (2025) · cites this paper as [4]
In the citing paper
“It is important to note that Grieves' definition of Digital Twin [6] does not apply to systems that show an Evolutionary Emergence, i.e., systems that exhibit a deliberate capability to learn and modify their behavior in order to adapt to changing conditions.”
From Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020) · cites this paper as [6]
In the citing paper
“If a user cannot distinguish a virtual product from a physical one, under appropriate simulation conditions, then a virtual representation of the physical object could be considered a Digital Twin [6].”
From Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020) · cites this paper as [6]
Citations
Cites
(1994) · Journal of the American Dietetic Association · doi:10.1016/0002-8223(94)92216-0 · Cited by 46,726
I.—COMPUTING MACHINERY AND INTELLIGENCE
TURING, A. M. (1950) · Mind · doi:10.1093/mind/lix.236.433 · Cited by 10,290
Computing Machinery and Intelligence (1950)
Turing, A. M. (2004) · doi:10.1093/oso/9780198250791.003.0017 · Cited by 6,120
Normal Accidents: Living with High Risk Technologies
Grimes, A. J., & Perrow, C. B. (1985) · Academy of Management Review · doi:10.2307/257982 · Cited by 4,985
Normal Accidents: Living with High-Risk Technologies
Cummings, L. L., & Perrow, C. (1984) · Administrative Science Quarterly · doi:10.2307/2392945 · Cited by 2,861
How Smart, Connected Products Are Transforming Competition
Porter, M. E., & Heppelmann, J. E. (2014) · Harvard business review · Cited by 2,600
The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles
Glaessgen, E., & Stargel, D. (2012) · 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA · doi:10.2514/6.2012-1818 · Cited by 2,404
Mitchell, M. (2009) · doi:10.1093/oso/9780195124415.001.0001 · Cited by 2,310
Towards a System of Systems Concepts
Ackoff, R. L. (1971) · Management Science · doi:10.1287/mnsc.17.11.661 · Cited by 1,204
Reengineering aircraft structural life prediction using a digital twin
Tuegel, E. J., Ingraffea, A. R., Eason, T. G., & Spottswood, S. M. (2011) · International Journal of Aerospace Engineering · doi:10.1155/2011/154798 · Cited by 1,119
Research works printed but not linked: 3
- Grieves, M. (2011). Virtually perfect: Driving innovative and lean products through product lifecycle management. Cocoa Beach, FL: Space Coast Press.
- Grieves, M. (2009). Virtually perfect: Driving innovative and lean products through product lifecycle management. Cocoa Beach, FL: Space Coast Press.
- Grieves, M. (2014). Process, practice, and innovation. In P. Gupta & B. Trusko (Eds.), Global innovation science handbook (pp. 159–172). New York: McGraw Hill Professional.
Cited by
Sorted by citations
Items 2,201–2,300 of 3,752
Neural Network Derivation of Optimal Digital Twins for Innovative Alloys and Composites
Burdina, А. A., Bobkov, I. A., Burdin, S. S., et al. (2023) · Russian Engineering Research · doi:10.3103/s1068798x23100040 · Cited by 2
LSTM-based digital twin prediction model for engine life
Li, J., & Wang, J. (2023) · IEEE International Conference on Networking, Sensing and Control (ICNSC) · doi:10.1109/icnsc58704.2023.10318980 · Cited by 2
Application of digital twin technology in Russia: Development opportunities and constraints
Sosfenov, D. A., & Shahova, M. S. (2023) · Economics and Management · doi:10.35854/1998-1627-2023-11-1325-1332 · Cited by 2
Ball and Beam Control Design based on a Fuzzy Digital Twin
P, F. A. T., Alejandro Velasquez, R., Velarde-Gomez, S., et al. (2023) · IEEE Colombian Conference on Automatic Control (CCAC) · doi:10.1109/ccac58200.2023.10333369 · Cited by 2
MemoryScan Environments: Creating Large-Scale Memory-Evocative Digital Twins
Walters, L. C., Michlowitz, R. A., Martinez, E. S., McMahan, R. P., & Kider, J. T. (2023) · IEEE International Conference on Digital Twins and Parallel Intelligence (DTPI) · doi:10.1109/dtpi59677.2023.10365482 · Cited by 2
Detecting Novel Behavior and Process Enhancement with Multimodal Process Mining
Telli, A., Erdoğan, T. G., & Kolukısa, A. (2023) · International Informatics and Software Engineering Conference (IISEC) · doi:10.1109/iisec59749.2023.10391012 · Cited by 2
Kim, J. H., & Lee, K. H. (2023) · Journal of the KNST · doi:10.31818/jknst.2023.12.6.4.387 · Cited by 2
Leveraging Digital Twins to Support a Sustained Human Presence on the Lunar Surface
Hua, E. Y., & Boan, L. M. (2023) · Winter Simulation Conference · doi:10.1109/wsc60868.2023.10407136 · Cited by 2
Digital Technologies for the Design of Human-Robot Collaborative Cells
Cella, C., Zanchettin, A. M., & Rocco, P. (2023) · IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE) · doi:10.1109/metroxraine58569.2023.10405765 · Cited by 2
Digital Twin for Smart Farming
Poornima, G., & A., S. G. M. (2024) · BENTHAM SCIENCE PUBLISHERS eBooks · doi:10.2174/9789815196177124010004 · Cited by 2
Construction of Digital Twin Battlefield with Command and Control as the Core
Wang, F., Ye, L., Zheng, S., et al. (2024) · Communications in computer and information science · doi:10.1007/978-981-97-0844-4_8 · Cited by 2
Luo, Y., & Ball, P. D. (2024) · Smart innovation, systems and technologies · doi:10.1007/978-981-99-8159-5_23 · Cited by 3
CMOR-DT: Tokamak device maintenance manipulator based on digital twin
Wan, C., Zuo, C., Zhang, X., et al. (2023) · IEEE Smart World Congress (SWC) · doi:10.1109/swc57546.2023.10449275 · Cited by 2
Evolution of Digital Twin solutions in the manufacturing industry
Mingorance, R., Crespo-Pereira, D., Uribetxebarria, J., & Leturiondo, U. (2023) · IEEE Smart World Congress (SWC) · doi:10.1109/swc57546.2023.10449254 · Cited by 2
Tao, H. (2024) · Theoretical and Natural Science · doi:10.54254/2753-8818/31/20241153 · 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
Anshari, M., Lim, S. A., & Semivolos, A. V. (2023) · International Conference on Sustaining Heritage: Innovative and Digital Approaches (ICSH) · doi:10.1109/icsh57060.2023.10482841 · Cited by 2
Pascali, M. (2024) · Frontiers in Sociology · doi:10.3389/fsoc.2024.1147627 · Cited by 2
A taxonomy of built asset information coupling
Davari, S., & Poirier, É. (2024) · Frontiers of Engineering Management · doi:10.1007/s42524-024-0303-7 · Cited by 2
A Data Structure for Developing Data-Driven Digital Twins
Orukele, O., Polette, A., Gonzalez-Lorenzo, A., et al. (2024) · IFIP advances in information and communication technology · doi:10.1007/978-3-031-62578-7_3 · Cited by 2
Biomimetic Regulation in Supply Chains and Production Systems
Thielen, M., Trube, N., Schneider, J. M., & von Ramin, M. (2024) · Advanced Intelligent Systems · doi:10.1002/aisy.202400049 · Cited by 2
Chakroun, A., Hani, Y., Mhamedi, A. E., & Faouzi Masmoudi, A. (2024) · Journal of Industrial Integration and Management · doi:10.1142/s2424862224500155 · Cited by 3
Casadei, R., Fornari, F., Mariani, S., & Savaglio, C. (2024) · Internet of things · doi:10.1007/978-3-031-62146-8_7 · Cited by 2
Kalla, D. K. (2024) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--46522 · Cited by 2
Dynamic Digital Twin Modeling towards Ship Operation and Maintenance Process
Guo, Z., Peng, L., Xu, W., et al. (2023) · International Conference on Computing and Big Data (ICCBD) · doi:10.1109/iccbd59843.2023.10607287 · Cited by 2
Digital Twin Architecture to Use for Optimizing an AoD-Printing Process
Pfannenstiel, H., Ungerer, M., & Sieber, I. (2024) · Symposium on Design, Test, Integration and Packaging of MEMS/MOEMS · doi:10.1109/dtip62575.2024.10613180 · Cited by 3
KURGUSAL EVRENDE SOSYAL ETKİLEŞİM VE SANAL KAYGI
Selçuk, N. (2024) · Adıyaman üniversitesi sosyal bilimler enstitüsü dergisi/Adıyaman üniversitesi sosyal bilimler enstitisü dergisi · doi:10.14520/adyusbd.1416279 · Cited by 2
Automation Processes for Efficient Verification of Complex Systems: An Empirical Case Study
Haugen, R. A., Skeie, N., & Müller, G. (2024) · Systems · doi:10.3390/systems13010017 · Cited by 2
Excuse me Sir/Madam, which Model?
Hällqvist, R., Herzog, E., Axehill, J. W., & Palmer, J. R. (2024) · INCOSE International Symposium · doi:10.1002/iis2.13225 · Cited by 2
Self-expanding City-Level Digital Twin Using Blockchain and IPFS
Kanai, K., Mine, A., Kanemitsu, H., et al. (2024) · Lecture notes on data engineering and communications technologies · doi:10.1007/978-3-031-72322-3_43 · Cited by 2
Development of a characterization and modeling method for Digital Twins in an assembly use case
Molter, J., Zimmer, S., Margies, L., et al. (2024) · Procedia CIRP · doi:10.1016/j.procir.2024.08.325 · Cited by 2
Galand, G., Rabah, S., Chapurlat, V., et al. (2024) · International Conference on Control, Decision and Information Technologies (CoDIT) · doi:10.1109/codit62066.2024.10708207 · Cited by 2
Nalepa, R., & Najdek, K. (2024) · International Power Electronics and Motion Control Conference (EPE-PEMC) · doi:10.1109/pemc61721.2024.10726372 · Cited by 2
On the Importance of Simulation and Digital Twin for Industrial Applications
Boschert, S., Heinrich, C., Malik, V., et al. (2024) · Simulation foundations, methods and applications · doi:10.1007/978-3-031-69107-2_5 · Cited by 2
Digital-Twin for Surgical Tool-Tissue Interaction: A Systems Perspective
Annamraju, S., Jeziorczak, P. M., Ye, Q., & Kim, I. (2024) · Annual Modeling and Simulation Conference (ANNSIM) · doi:10.23919/annsim61499.2024.10732565 · Cited by 2
Digital Evolution: From BIM to Digital Twin
Salzano, A., Zitiello, E. P., Nicolella, M., & Gragnaniello, C. (2024) · Lecture notes in civil engineering · doi:10.1007/978-3-031-71867-0_46 · Cited by 2
Digital twin model design for smart village
Ahmad, N., Fatima, I., Alam, M., Khan, I. R., & Mahmoud, A. (2024) · Elsevier eBooks · doi:10.1016/b978-0-443-28884-5.00006-3 · Cited by 5
How 6G and AI Can Reshape the Future of Electric Systems
Zavodovski, A., Aghdam, F. H., Caló, A., Dehkordi, R., Štěpánek, P., Rasti, M., Pongrácz, É., & Ahokangas, P. (2024) · IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) · doi:10.1109/eeeic/icpseurope61470.2024.10751181 · Cited by 2
POPOV, I. A. J., Popov, I. A., Gureev, V. M., et al. (2024) · Journal of Engineering Physics and Thermophysics · doi:10.1007/s10891-024-03066-y · Cited by 2
POPOV, I. A. J., Zhukova, Y. V., CHORNY, A. D., BARANOVA, T. A., KUKHARCHUK, I. G., MEDVEDEV, V. M., & POPOV, I. A. J. (2024) · Mechanics of Machines Mechanisms and Materials · doi:10.46864/1995-0470-2024-4-69-28-38 · Cited by 2
Bökle, S., Gscheidle, M., Weis, M., et al. (2024) · Smart Agricultural Technology · doi:10.1016/j.atech.2024.100701 · Cited by 2
Khoo, T. K., Wang, J., Esa, M. B., & Sun, J. (2024) · Journal of Advanced Research in Applied Sciences and Engineering Technology · doi:10.37934/araset.53.2.283298 · Cited by 2
Model-Based Engineering of Multi-Purpose Digital Twins in Manufacturing
Heithoff, M., Jansen, N., Michael, J., Rademacher, F., & Rumpe⋆, B. (2024) · Springer eBooks · doi:10.1007/978-3-031-67778-6_5 · Cited by 2
A dataset to test AI on forensic scenes
Daudigny, H., & Grussenmeyer, P. (2024) · The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences · doi:10.5194/isprs-archives-xlviii-2-w8-2024-117-2024 · Cited by 2
Application of Digital Twins for Design and Operation of a Power Electronic Devices
Hinov, N. L., Stanchev, P. A., & Vacheva, G. I. (2024) · doi:10.1109/telecom63374.2024.10812225 · Cited by 2
Sensors and Metaverse-Digital Twin Integration: A Path for Sustainable Smarter Cities
Sahraoui, Y., & Kerrache, C. A. (2024) · Internet of things · doi:10.1007/978-3-031-72732-0_3 · Cited by 2
Using IoT Enabled Predictive Maintenance to Enhance Business Operations: Benefits and Challenges
Ansari, S., & Ansari, A. (2024) · Global Conference on Wireless and Optical Technologies (GCWOT) · doi:10.1109/gcwot63882.2024.10805626 · Cited by 2
Review on Digital Twin in Pharmaceutical and Biopharmaceutical Manufacturing
Ghavat, K., Wakchoure, S., Surve, P., & Hole, N. (2024) · International Journal of Scientific Research in Science and Technology · doi:10.32628/ijsrst241161127 · Cited by 2
Farahani, N. I., Lin, L. D., Nazir, S., Naderi, A., Rokos, L., McIntosh, A. R., & Julian, L. M. (2025) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2024.1478572 · Cited by 4
Ye, F., Jin, Z., Zhang, P., Xu, D., Lin, L., & Sun, J. Q. (2025) · International Journal of Intelligent Systems · doi:10.1155/int/8899669 · Cited by 2
Hatagi, T., Miyake, M., & Kameda, S. (2024) · International Conference on Information and Communication Technology Convergence (ICTC) · doi:10.1109/ictc62082.2024.10827268 · Cited by 2
Educational Digital Twin: Tackling Complexity in Educational Big Data
Huang, L., & Willcox, K. E. (2024) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata62323.2024.10825338 · Cited by 2
Barat, S., Yadav, A., Thogaru, H., Kulkarni, V., & Bhattacharya, K. (2024) · Winter Simulation Conference · doi:10.1109/wsc63780.2024.10838620 · Cited by 2
The Convergence of Artificial Intelligence and Big Data for Humanitarian Supply Chain Resilience
Ahatsi, E., Akpan, J. S., & Olanrewaju, O. A. (2024) · doi:10.1109/ihtc61819.2024.10855125 · Cited by 2
Dhivya, K. (2025) · IGI Global eBooks · doi:10.4018/979-8-3693-4199-5.ch005 · Cited by 2
Risk response capability assessment for the digital twin-based human–robot collaboration
Liu, X., Li, G., Xiang, F., et al. (2025) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-025-15190-x · Cited by 2
Vadisetty, R., & Polamarasetti, A. (2024) · International Conference on System Modeling & Advancement in Research Trends (SMART) · doi:10.1109/smart63812.2024.10882564 · Cited by 2
Towards dynamic Visualization of Digital Twins in Engineering
Jaenicke, M., Bender, J., & Ovtcharova, J. (2025) · Procedia Computer Science · doi:10.1016/j.procs.2025.01.093 · Cited by 2
METHODOLOGICAL ASPECTS OF INNOVATIVE DEVELOPMENT OF BUSINESS PROCESSES OF ENTERPRISES
Вініченко, І. І., Polehenka, M., & Diachenko, N. (2025) · Економіка та суспільство · doi:10.32782/2524-0072/2025-71-36 · Cited by 2
Zimmer, S., Molter, J., Margies, L., et al. (2025) · Springer eBooks · doi:10.1007/978-3-031-74010-7_6 · Cited by 2
Digital Twin: Graph Formulations for Managing Complexity and Uncertainty
Huang, L., Kapteyn, M. G., & Willcox, K. E. (2024) · IEEE Smart World Congress (SWC) · doi:10.1109/swc62898.2024.00327 · Cited by 2
Yu, W., Wu, J., Yu, Y., et al. (2024) · International Symposium on Artificial Intelligence and Intelligent Manufacturing (AIIM) · doi:10.1109/aiim64537.2024.10934453 · Cited by 2
Digital Twin technologies in enhancing supply chain resilience
Xu, L., & de Vrieze, P. T. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-30076-9.00015-7 · Cited by 2
IDLE: A Digital Twin Framework for 6G Network Intelligence
Caruso, A. O., Grasso, C., Raftopoulos, R., et al. (2024) · IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD) · doi:10.1109/camad62243.2024.10942700 · Cited by 2
Owais, O. A., Poshdar, M., GhaffarianHoseini, A., Ying, F., Jaafar, K., Sarhan, S., & Sheikhkhoshkar, M. (2025) · Lecture notes in civil engineering · doi:10.1007/978-981-96-4051-5_62 · Cited by 2
Beitelmal, W. H., & Alruwaythi, O. (2025) · Arabian Journal for Science and Engineering · doi:10.1007/s13369-025-10207-9 · Cited by 2
Digital Twins to Support Smart Manufacturing System Design and Ramp up
van Ginkel, M., Yazdi, P. G., Rupert, T., et al. (2025) · Procedia CIRP · doi:10.1016/j.procir.2025.02.221 · Cited by 2
Inginshetty, A., Bellure, S., de Ocaña, A. S., & Fathi, M. (2025) · Procedia CIRP · doi:10.1016/j.procir.2025.02.162 · Cited by 4
LOJİSTİK SEKTÖRÜNDE DİJİTAL İKİZ UYGULAMALARI
AKÇACI, T., & Tanır, Y. M. (2025) · Econder International Academic Journal · doi:10.35342/econder.1693393 · Cited by 2
Data collection method for creating digital twin of planted forests
Sukhanov, Y., & Vasilev, A. S. (2025) · Glasnik srpskog geografskog drustva · doi:10.2298/gsgd2501127s · Cited by 2
Flett, G., Tuohy, P. G., Howorth, G., et al. (2025) · Sustainable Energy Grids and Networks · doi:10.1016/j.segan.2025.101924 · Cited by 2
On Designing Evolving Cyber–Physical–Social Systems: A Decision-Based Design Perspective
Gupta, H. K., Bhalerao, M. J., Honeycutt, W. T., Allen, J. K., & Mistree, F. (2025) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4070094 · Cited by 2
Systematic selection framework for digital twin development environments in smart manufacturing
Dodero, C., McCormick, M. R., Malik, A. A., et al. (2025) · Digital Twin · doi:10.1080/27525783.2025.2565246 · Cited by 2
Reimagining Supply Chain Planning Using Machine Learning: A Roadmap to Agility and Resilience
Cohen, M. A., Agrawal, N., & Deshpande, V. (2025) · Springer series in supply chain management · doi:10.1007/978-3-032-07054-8_11 · Cited by 2
Tiwari, A. (2026) · International Journal of Urban Sciences · doi:10.1080/12265934.2026.2647852 · Cited by 2
Multimodal Data Representation Model for Complex Description of Observation Objects
Dychka, I. A., & Sulema, Y. S. (2020) · Visnyk of Vinnytsia Politechnical Institute · doi:10.31649/1997-9266-2020-148-1-53-60 · Cited by 2
ENGINEERING AND CONSTRUCTION PROJECT MANAGEMENT IN THE DIGITAL TWIN ERA
Patias, I. (2020) · Proceedings of CBU in Natural Sciences and ICT · doi:10.12955/pns.v1.127 · Cited by 2
Fault Diagnosis in a Hydraulic Circuit Using a Support Vector Machine Trained by a Digital Twin
Haas, R., & Pichler, K. (2021) · Advanced structured materials · doi:10.1007/978-3-030-79325-8_5 · Cited by 2
Informing Value: industry analysis for complex process facility digital twins
McNair, R. (2022) · Muma Business Review · doi:10.28945/4937 · Cited by 4
Addressing the Complexity Challenge with Adaptive Verification and Validation
Felder, W. N. (2019) · American Institute of Aeronautics and Astronautics eBooks · doi:10.2514/5.9781624105654.0121.0150 · Cited by 2
A Calculus of Space, Time, and Causality: Its Algebra, Geometry, Logic
Hoare, T., Struth, G., & Woodcock, J. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-31038-7_1 · Cited by 2
MODELS OF COMPUTATION FOR DIGITAL TWINS DATA PROCESSING
Sulema, Y. S., & Rvach, D. V. (2020) · KPI Science News · doi:10.20535/kpi-sn.2020.2.205131 · Cited by 2
The Characteristics of Digital Twin in Cyberspace: A Knowledge Perspective
Ling, W.-Q., & Guan, W. (2019) · International Conference Data Science and Business Analytics · doi:10.1109/icdsba48748.2019.00032 · Cited by 4
The Evolution from Digital Mock-Up to Digital Twin
Dai, S., Zhao, G.-H., Yu, Y., & Bao, Q.-W. (2020) · International Conference on Machine Learning and Intelligent Systems · doi:10.3233/faia200781 · Cited by 2
The formation of a Digital Twin of a complex electrical engineering object
Mustaev, I., Semivelitchenko, E., Ivanov, V. V., & Mustaev, T. I. (2020) · International Conference on Electrotechnical Complexes and Systems (ICOECS) · doi:10.1109/icoecs50468.2020.9278481 · Cited by 2
Shahriar, M. R., Liu, X. F., Rahman, M. M., & Sunny, S. M. N. A. (2020) · IEEE International Conference on Services Computing · doi:10.1109/scc49832.2020.00024 · Cited by 2
Past and Future Perspectives on Digital Twin Research at SOHOMA
Kruger, K., Redelinghuys, A. J. H., Basson, A. H., et al. (2021) · Studies in computational intelligence · doi:10.1007/978-3-030-69373-2_5 · Cited by 2
Stateful Stream Processing Containerized as Microservice to Support Digital Twins in Fog Computing
Alaasam, A. B. A., Radchenko, G., Tchernykh, A. N., et al. (2021) · Proceedings of the Institute for System Programming of RAS · doi:10.15514/ispras-2021-33(1)-5 · Cited by 2
Bi, Z. (2021) · Springer eBooks · doi:10.1007/978-3-030-70304-2_6 · Cited by 2
Engels, G. (2021) · International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS) · doi:10.1109/seams51251.2021.00045 · Cited by 2
Life Cycle of a Digital Resource Twin: Meta-Modeling and Application Example
Sjarov, M., Lechler, T., Russwurm, E., Fuchs, J., Faltus, F., Schäffer, E., Brossog, M., & Franke, J. E. (2021) · Procedia CIRP · doi:10.1016/j.procir.2021.11.277 · Cited by 2
At Home AND Together? Virtual Event Twins und Virtual Event Substitutes als Coronabuster
Bär, S. (2022) · Markenkommunikation und Beziehungsmarketing · doi:10.1007/978-3-658-35165-6_6 · Cited by 2
Frontiers in computing for artificial intelligence
Humble, T. S., Perdue, G., Fahim, F., Lamm, H., & Schram, M. (2022) · Journal of Instrumentation · doi:10.1088/1748-0221/17/03/c03037 · Cited by 2
Virtual Reality Extension for Digital Twins of Machine Tools
Holzwarth, V., Hirt, C., Gisler, J., et al. (2022) · Progress in IS · doi:10.1007/978-3-030-97042-0_8 · Cited by 2
Digital Twins in Russian Metallurgy: Prerequisites and Limitations of Use
Romanova, O. V., & Sirotin, D. V. (2022) · Lecture notes in information systems and organisation · doi:10.1007/978-3-030-94617-3_5 · Cited by 2
Krämer, M., Bender, T., Bock, N., et al. (2022) · Springer eBooks · doi:10.1007/978-3-658-36266-9_4 · Cited by 2
Definitions and principles of digital twins
Fang, Z., Lu, Q., Xie, X., Parlikad, A. K., Schooling, J. M., & Pitt, M. (2022) · doi:10.1680/dtbe.65802.005 · Cited by 2
Integration of a Digital Twin into Production Line Control
Burčiar, F., & Važan, P. (2022) · Lecture notes in networks and systems · doi:10.1007/978-3-031-09073-8_26 · Cited by 2
Optimal graph partitioning for time-sensitive flow scheduling towards digital twin networks
Wang, S., Kua, J., Jin, J., Kulkarni, A., Jayaraman, P. P., & Cao, X. (2022) · doi:10.1145/3566099.3569003 · Cited by 3
Construction Method and Application Prospect of Electrical Machine Digital Twin
Liu, L., Guo, Y. G., Lei, G., Yin, W., Ba, X., & Zhu, J. G. (2022) · International Conference on Electrical Machines and Systems (ICEMS) · doi:10.1109/icems56177.2022.9983289 · Cited by 2
Metadata
- Authors
- Grieves, M., & Vickers, J.
- Affiliations
- Florida Institute of Technology (US)
- Marshall Space Flight Center (US)
- Corresponding author
- Grieves, Michael
- Venue
- Transdisciplinary Perspectives on Complex Systems
- Publisher
- Springer International Publishing
- Published
- 2016-08-17
- Pages
- 85-113
- OpenAlex
- W2518003110
- Semantic Scholar
- 157d07292ffadb2c17d100f5b0471b356868ab3e
- Cited by
- 3,727
- References
- 32
- Citations by year
- 2026: 697 · 2025: 743 · 2024: 619 · 2023: 580 · 2022: 431 · 2021: 296 · 2020: 187 · 2019: 113 · 2018: 47 · 2017: 12 · 2016: 2
- FWCI
- 138.63
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Springer eBooks (publishedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Systems Engineering Methodologies and Applications
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Social Sciences › Decision Sciences › Management Science and Operations Research › Complex Systems and Decision Making
- Keywords
- digital twin, emergent behavior, complex systems, product life cycle, systems engineering, normal accidents, human interaction, front-running, NASA
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
