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Digital Twin: Origin to Future
Open accessAbstract
Digital Twin (DT) refers to the virtual copy or model of any physical entity (physical twin) both of which are interconnected via exchange of data in real time. Conceptually, a DT mimics the state of its physical twin in real time and vice versa. Application of DT includes real-time monitoring, designing/planning, optimization, maintenance, remote access, etc. Its implementation is expected to grow exponentially in the coming decades. The advent of Industry 4.0 has brought complex industrial systems that are more autonomous, smart, and highly interconnected. These systems generate considerable amounts of data useful for several applications such as improving performance, predictive maintenance, training, etc. A sudden influx in the number of publications related to ‘Digital Twin’ has led to confusion between different terminologies related to the digitalization of industries. Another problem that has arisen due to the growing popularity of DT is a lack of consensus on the description of DT as well as so many different types of DT, which adds to the confusion. This paper intends to consolidate the different types of DT and different definitions of DT throughout the literature for easy identification of DT from the rest of the complimentary terms such as ‘product avatar’, ‘digital thread’, ‘digital model’, and ‘digital shadow’. The paper looks at the concept of DT since its inception to its predicted future to realize the value it can bring to certain sectors. Understanding the characteristics and types of DT while weighing its pros and cons is essential for any researcher, business, or sector before investing in the technology.
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“In accordance with DT characteristics, the DTP is able to simulate manufacturing scenarios and perform validation testing, evaluation and even quality control testing prior to the actual manufacturing process itself.This approach effectively reduces production costs and operational time by identifying flaws or possible risks of the physical twin before production.”
From Digital Twin Technology Challenges and Applications: A Comprehensive Review (2022) · cites this paper as [10]
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“It is important to note that the development and widespread implementation of DTs depend on the advances in research and enabling technologies such as AI, ML, big data, 5G communication and cloud/edge computing [10,83].”
From Digital Twin Technology Challenges and Applications: A Comprehensive Review (2022) · cites this paper as [10]
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In the citing paper
“The proposed approach involved utilizing DT technology to replicate the aircraft's physical and mechanical characteristics, aiming to forecast potential fatigue or structural cracks.This strategy would effectively extend the operational lifespan of the aircraft [21].”
From Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0 (2025) · cites this paper as [21]
The cited source says what the claim attributes to it.
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“Furthermore, the continuous transfer of information between DT and its physical counterpart enables ongoing validation and optimization of the system's processes [21].”
From Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0 (2025) · cites this paper as [21]
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“However, the modern state of the art classifies and defines DTs based on the application domain [10] and their levels of integration.”
From Digital Twin Technology Challenges and Applications: A Comprehensive Review (2022) · cites this paper as [10]
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“High costs of implementation due to the increased amount of sensors and computational resources needed [10,18].”
From Digital Twin Technology Challenges and Applications: A Comprehensive Review (2022) · cites this paper as [10]
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“Issues related to data (trust, privacy, cybersecurity, convergence and governance, acquisition and large-scale analysis) [10].”
From Digital Twin Technology Challenges and Applications: A Comprehensive Review (2022) · cites this paper as [10]
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Citations
Cites
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Kim, J., lee, W., & Kim, E. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4616355
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Methodda Silva, I. N., Hernández‐Jayo, U., & García-Zubía, J. (2023) · Lecture notes in networks and systems · doi:10.1007/978-3-031-42467-0_18
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Eslahi, M., Farazdaghi, E., & Meouche, R. E. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-54376-0_18 · Cited by 1
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“From another perspective, DTs can also be categorized according to their place in a hierarchy [9], e.g. in a city-wide DT: 1) Unit Level : A DT for the smallest units of city-scale DT, like vehicles and buildings.”
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“[1,2] .”
Gelecek, Metaverse ve Yapım Endüstrisi
Akturan, E., & Kasapoğlu, E. (2024) · Kocaeli Üniversitesi Mimarlık ve Yaşam Dergisi · doi:10.26835/my.1380066
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Digital Twin for Ion Mobility Spectrometry Devices
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Üniversite Öğrencilerinin METAVERSE Algıları
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“Originally introduced for use in spacecraft by the National Aeronautics and Space Administration (NASA), DTs have been extensively embraced by a number of industries, including manufacturing, urban planning, healthcare, and the automobile sector [3], [4].”
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Building a University Digital Twin
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Advances and Challenges of Digital Twin Technology in Urban Drainage Systems
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Multiphysics Acausal Modeling and Simulation of Satellites using a Modelica Library
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Improving schedule accuracy of a reconfigurable assembly system
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Concept of a Virtual Test Field for Inland Waterway Transport
Sutanto, J., Hürten, C., Jarofka, M., Kracht, F. E., & Schramm, D. H. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-84148-4_15
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“The work of [5] gives an overview of DT technology in various applications.”
Integrating Drones With Digital Twins for Aerial Remote Sensing
Al‐Darraji, I., Khan, F. Q., Salim, T. T., Tsaramirsis, G., Jerbi, H., Kakei, A., & Ismaeel, A. G. (2025) · Radio Science · doi:10.1029/2023rs007700
“On the other hand, the term Digital Twin (DT) refers to a 3D digital copy of a real‐world product or operation (Singh et al., 2021).”
Caldana, V. M., Fumagalli, L., & Godoy, E. P. (2025) · International Conference on Industrial Engineering and Operations Management (IEOM) · doi:10.46254/sa6.20250091
Maturity Models for Digital Twins in Smart Cities – Literature Review and Comparison
Hartmann, M., & Wimmer, M. A. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-01589-1_17
Digital Twin for a Semiautomatic Carbonated Water Packaging Machine
Puente, M., Moya, M. J., Mosquera, G., Abedrabbo, F., & Vera, K. L. C. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-98290-3_14
Comparative Analysis of Mapping Methods Used in Interior Space Organization and Experience Design
Keçeli, M., & Ergin, G. (2025) · PLANARCH - Design and Planning Research · doi:10.54864/planarch.1648358
Digital Twin prototype to support Factory and Production Planning
Raheem, A., Dallasega, P., Kaushal, I., Revolti, A., & Suni, H. A. M. (2025) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2025.09.159
Raheem, A., Dallasega, P., Kaushal, I., Suni, H. A. M., & Baumgartner, F. (2025) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2025.09.158
Palma, A. L., Flamini, A., Galasso, A., Nissim, R., Notte, L. L., & Pietra, B. D. (2025) · IEEE International Conference on Environment and Electrical Engineering and IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) · doi:10.1109/eeeic/icpseurope64998.2025.11169149
Calabrese, M., Primo, T., & Prete, A. D. (2025) · International Journal of Modelling and Simulation · doi:10.1080/02286203.2025.2563984
Meharg, P., James, S. C., & Dudash, A. (2025) · INCOSE International Symposium · doi:10.1002/iis2.70062
Nguyễn, T. A., Lim, D., Nam, S., Min, D., Fé, I., Silva, F. A., & Maciel, P. R. M. (2025) · IEEE International Conference on Metaverse Computing, Networking and Applications (MetaCom) · doi:10.1109/metacom65502.2025.00020
“A metaverse hosted on a cloud-edge continuum supplies the scale and low-latency interaction needed for such twins: cloud nodes execute compute-heavy physics and AI, while edge nodes close the loop for tele-operation and pilot interfaces [1, 4, 7].”
InfluentialZhang, M., Li, G., He, C., Wang, Y., Luan, T. H., & Liang, H. (2025) · IEEE International Conference on Metaverse Computing, Networking and Applications (MetaCom) · doi:10.1109/metacom65502.2025.00055
Semantic Support in Standardized Environments
Spieldenner, D., Antakli, A., Spieldenner, T., & Sahota, H. (2025) · Communications in computer and information science · doi:10.1007/978-3-032-06878-1_10
Application of Industry 4.0 Technologies for Marine Internal Combustion Engines Diagnostic Systems
Мinchev, D., Варбанець, Р. А., & Kucherenko, Y. (2025) · Studies in systems, decision and control · doi:10.1007/978-3-032-05884-3_14
National Strategies and Practices for the Metaverse Development: The Case of Finland
Jauhiainen, J. S. (2025) · Applied innovation and technology management · doi:10.1007/978-3-031-97080-1_8
The impact of IoT on LCA's primary energy indicator
Barros, N. N., Dias, A. M., Ziza, L. N., Lisboa, D. C., Ximenes, T. S. D. S., Gonzalez, L. F. G., & Ruschel, R. C. (2025) · PARC Pesquisa em Arquitetura e Construção · doi:10.20396/parc.v16i00.8674118
Wang, Y., Jing, L., Wang, Y.-C., Jiang, W., Wang, C., Fan, B., Zhou, X., & Li, X. (2025) · IEEE International Conference on High Performance Computing and Communications; IEEE International Conference on Smart City; IEEE International Conference on Data Science and Systems (HPCC/SmartCity/DSS) · doi:10.1109/hpcc67675.2025.00217
“This approach enables functions like bidirectional data mapping and dynamic simulation of production operations, thereby enhancing production process optimization and supporting informed decision-making [5].”
Sharma, V. K., Sharma, A., Giri, J. P., Al-Qawasmi, K. E., Sunheriya, N., & Chadge, R. (2025) · Studies in systems, decision and control · doi:10.1007/978-3-031-89771-9_20
CUP model: Purpose-driven digital twin configuration through enhanced user engagement
Vos, R., Schepers, J., Raassens, N., & Langerak, F. (2026) · Journal of business research · doi:10.1016/j.jbusres.2025.115809
Unveiling the path to digital twin development models: a systematic review
Shafiee, S., & Ayat, M. (2025) · International Journal of Systems Assurance Engineering and Management · doi:10.1007/s13198-025-03037-3
“In aviation, General Electric (GE) uses DTs for real-time engine monitoring and predictive maintenance, resulting in greater reliability and lower operating costs (Singh et al. 2021).”
Bio-Flocculants for Wastewater Treatment Using Machine Learning Approach
Sharma, A., Srivastava, S., Sharma, I., Sharma, M., Gora, S., & Monika, M. (2025) · Springer eBooks · doi:10.1007/978-981-96-9764-9_20 · Cited by 1
Elkabalawy, M., Zeynolabedini, S., Han, S., & Ma, J. W. (2025) · ASCE International Conference on Computing in Civil Engineering (i3CE) · doi:10.1061/9780784486122.046
Digital twin for smart wireless sensor networks
Keshmiry, A., & Hassani, S. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-33441-2.00013-6 · Cited by 1
Controlling and Interacting with Robot’s Digital Twin: a Literature Review
Sobota, T., Korečko, Š., & Sobota, B. (2025) · International Conference on Emerging eLearning Technologies and Applications (ICETA) · doi:10.1109/iceta67772.2025.11280300
“The first detailed definition of a DT was provided by NASA in an article by M. Shafto [8].”
Kouam, A. W. F. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5509249
Role of Machine Leaning in D2D Communication in 6G
Khan, H., Alam, M. Z., Khan, M. R., Alam, M. I., Siddiuqi, S. T., & Salim, A. (2025) · Communications in computer and information science · doi:10.1007/978-3-032-06198-0_10
Szczeblewski, S., & Gębicki, J. (2025) · Chemical Product and Process Modeling · doi:10.1515/cppm-2025-0166
Efficient Data Encryption Scheme Based CP-ABE for Digital Twin Network in 6G
Yan, R., Su, L., Du, H., & Wang, K. (2025) · World Symposium on Communication Engineering (WSCE) · doi:10.1109/wsce68305.2025.11300674
“With the rapid development of communication and AI technologies, digital twin technology research has become a hot spot, and has been successfully applied in smart manufacturing, smart energy, smart mobility, and smart healthcare and so on[3-6].”
DİJİTAL İKİZ UYGULAMALARI VE MALİYETLERE BÜTÜNCÜL YAKLAŞIM
Özyürek, H., & Yurdakul, H. (2025) · Niğde Ömer Halisdemir Üniversitesi Sosyal Bilimler Enstitüsü Dergisi · doi:10.56574/nohusosbil.1463350
Bing, Y., Mokhtar, S. B., & bin Shahlal, N. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2594745
“Digital simulation mainly adopts dynamic virtual models of physical entities or processes to synchronize data and simulate behaviors in real time (Singh et al., 2021); reinforcement learning dynamically adjusts decision-making through trial-and-error learning strategies with the goal of maximizing…”
Metadata
- Authors
- Singh, M., Fuenmayor, E., Hinchy, E., Qiao, Y., Murray, N., & Devine, D.
- Affiliations
- Athlone Institute of Technology (IE)
- University of Limerick (IE)
- Corresponding author
- Devine, Declan
- Venue
- Applied System Innovation
- Publisher
- MDPI AG
- Published
- 2021-05-24
- Volume
- 4
- Issue
- 2
- Pages
- 36
- ISSN
- 2571-5577 (ISSN-L)
- OpenAlex
- W3164800436
- Cited by
- 1,038
- References
- 72
- Citations by year
- 2026: 189 · 2025: 275 · 2024: 260 · 2023: 198 · 2022: 102 · 2021: 14
- FWCI
- 74.25
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Applied System Innovation (publishedVersion, cc-by)
- University of Limerick Institutional Repository (University of Limerick) (acceptedVersion, other-oa)
- Arrow@dit (Dublin Institute of Technology) (submittedVersion, cc-by-nc-sa)
- Research@THEA (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by-nc-sa)
- Funders
- Science Foundation Ireland (16/RC/3918)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Applied Advanced Technologies
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Digital Innovation in Industries
- Keywords
- digital twin, physical twin, Industry 4.0, real-time data exchange, predictive maintenance, digital thread, digital models, digital shadow, terminology confusion, industrial digitalization
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