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
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“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.
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Qamsane, Y., Balta, E. C., Moyne, J. R., Tilbury, D. M., & Barton, K. L. (2019) · Proceedings of the ... American Control Conference/Proceedings of the American Control Conference · doi:10.23919/acc.2019.8814412 · Cited by 31
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Guo, F., Liu, J., Zou, F., Yunong, Z., Zhongqi, W., & Shaozhuo, L. (2019) · Journal of Mechanical Engineering · doi:10.3901/jme.2019.17.110 · Cited by 30
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Oehlschläger, D., Glas, A. H., & Eßig, M. (2023) · Industrial Management & Data Systems · doi:10.1108/imds-07-2023-0467 · Cited by 32
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Metcalfe, B., Boshuizen, H., Bulens, J., & Koehorst, J. (2023) · F1000Research · doi:10.12688/f1000research.137262.1 · Cited by 29
Aggarwal, P., Narwal, B., Purohit, S., et al. (2023) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2023.108889 · Cited by 29
In situ virtual sensors in building digital twins: framework and methodology
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Zhang, Z., Qu, T., Huang, G. Q., Zhao, K., Zhang, K., Li, M., Zhang, Y., Liu, L., & Zhong, H. (2024) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2024.08.004 · Cited by 32
Fault diagnosis method for oil-immersed transformers integrated digital twin model
Yao, H., Zhang, X., Guo, Q., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-71107-w · Cited by 29
Lucchi, E. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-34174-8.00026-0 · Cited by 29
Industrial applications of digital twins: A systematic investigation based on bibliometric analysis
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Riss, U., Maus, H., Javaid, S., & Jilek, C. (2020) · The Practice of Enterprise Modeling · doi:10.1007/978-3-030-63479-7_3 · Cited by 17
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Land, M., Thürer, M., Stevenson, M., Fredendall, L. D., & Scholten, K. (2021) · Journal of Operations Management · doi:10.1002/joom.1133 · Cited by 31
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Abbate, R., Caterino, M., Fera, M., & Caputo, F. (2022) · Procedia Computer Science · doi:10.1016/j.procs.2022.01.252 · Cited by 29
Nguyen, H. D., & Tran, K. P. (2023) · Springer series in reliability engineering · doi:10.1007/978-3-031-30510-8_2 · Cited by 35
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Li, M., Chen, C., Yang, X., Zhou, J. T., Zhang, T., & Li, Y. (2023) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2023.3310089 · Cited by 29
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Yan, K. K., Xu, W., Yao, B., Zhou, Z., & Pham, D. T. (2018) · Communications in computer and information science · doi:10.1007/978-981-13-2853-4_26 · Cited by 29
Exploiting Factory Telemetry to Support Virtual Reality Simulation in Robotics Cell
Kuts, V., Modoni, G. E., Terkaj, W., Tähemaa, T., Sacco, M., & Otto, T. (2017) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-60922-5_16 · Cited by 38
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Karakra, A., Fontanili, F., Lamine, E., et al. (2022) · Digital Twin · doi:10.12688/digitaltwin.17454.1 · Cited by 28
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Three research priorities for just and sustainable urban systems: Now is the time to refocus
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Tian, H.-M., & Wang, Y. (2023) · Computers and Geotechnics · doi:10.1016/j.compgeo.2023.105953 · Cited by 25
Towards A Reasoning Framework for Digital Clones Using the Digital Thread
Miled, Z. B., & French, M. O. (2017) · AIAA Aerospace Sciences Meeting · doi:10.2514/6.2017-0873 · Cited by 25
Jawad, M. S., Chandran, P., Ramli, A. A., Mahdin, H., Abdullah, Z. B., & Rejab, M. M. (2022) · MethodsX · doi:10.1016/j.mex.2022.101920 · Cited by 24
Digital Twin Applications in Manufacturing Industry: A Case Study from a German Multi-National
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Hermon, S., Niccolucci, F., Bakirtzis, N., et al. (2023) · Journal of Cultural Heritage · doi:10.1016/j.culher.2023.11.004 · Cited by 24
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
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