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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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“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]
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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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“…literature have referred to DT as a virtual or digital model [21,23,27–35], layout [36], counterpart [7,9,35,37], doppelganger [38], clone [39], footprint [40], software analogue [41], representation [42–46], information constructs [2,47], or simulation [20,26,48–51] of its physical counterpart.”
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Flagged first, then by citations
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Items 101–200 of 1,000
Digital twin in the chemical industry: A review
Mane, S., Dhote, R. R., Sinha, A., & Raja, T. (2024) · Digital twins and applications. · doi:10.1049/dgt2.12019 · Cited by 51
Korotkova, N., Benders, J., Mikalef, P., & Cameron, D. (2023) · Information & Management · doi:10.1016/j.im.2023.103787 · Cited by 53
Model-based data integration along the product & service life cycle supported by digital twinning
Woitsch, R., Sumereder, A., & Falcioni, D. (2022) · Computers in Industry · doi:10.1016/j.compind.2022.103648 · Cited by 50
Luo, J., Liu, P., & Cao, L. (2022) · ISPRS International Journal of Geo-Information · doi:10.3390/ijgi11080452 · Cited by 53
Mügge, J., Erdmann, J. G., Riedelsheimer, T., Manoury, M., Smolka, S.-O., Wichmann, S., & Lindow, K. (2023) · Sustainability · doi:10.3390/su15097187 · Cited by 49
An Approach to Develop Digital Twins in Industry
González-Herbón, R., González-Mateos, G., Ossorio, J. R. R., Domínguez, M., Alonso, S., & Fuertes, J. J. (2024) · Sensors · doi:10.3390/s24030998 · Cited by 55
“…the future process, it is called Prototype DT; if, in contrast, it is used as a digital model of a specific system element, it is named Instance DT; if it is a set of system elements, it is defined as Aggregate DT, and if it is a set of Aggregate DTs, it forms what is known as Augmented DT [7,17].”
BackgroundMethodImplementations of Digital Transformation and Digital Twins: Exploring the Factory of the Future
Rahmani, R., Jesus, C., & Lopes, S. I. (2024) · Processes · doi:10.3390/pr12040787 · Cited by 58
A review on machine learning applications in hydrogen energy systems
Allal, Z., Noura, H., Salman, O., Vernier, F., & Chahine, K. (2025) · International Journal of Thermofluids · doi:10.1016/j.ijft.2025.101119 · Cited by 50
The Metaverse: Innovations and generative AI
Jauhiainen, J. S. (2024) · International Journal of Innovation Studies · doi:10.1016/j.ijis.2024.04.004 · Cited by 59
Sacoto-Cabrera, E. J., Pérez‐Torres, A., Tello-Oquendo, L., & Cerrada, M. (2025) · Smart Cities · doi:10.3390/smartcities8050175 · Cited by 73
“In this context, cutting-edge technologies such as Digital Twins (DTw) [4], IoT [5–7], and AI [8], have emerged as key enablers of Digital Transformation (DT) [9,10], revolutionizing urban planning and management.”
Probabilistic machine learning based predictive and interpretable digital twin for dynamical systems
Tripura, T., Desai, A. S., Adhikari, S., & Chakraborty, S. (2023) · Computers & Structures · doi:10.1016/j.compstruc.2023.107008 · Cited by 47
Rahman, H., Shah, U. M., Riaz, S. M., Kifayat, K., Moqurrab, S. A., & Yoo, J. (2024) · Future Generation Computer Systems · doi:10.1016/j.future.2024.03.023 · Cited by 47
Hafeez, M. A., Procacci, A., Coussement, A., & Parente, A. (2024) · Resources Conservation and Recycling · doi:10.1016/j.resconrec.2024.107796 · Cited by 50
A Retrieval-Augmented Generation Approach for Data-Driven Energy Infrastructure Digital Twins
Ieva, S., Loconte, D., Loseto, G., Ruta, M., Scioscia, F., Marche, D., & Notarnicola, M. (2024) · Smart Cities · doi:10.3390/smartcities7060121 · Cited by 52
Almadhor, A. S., Ghazouani, N., Bouallègue, B., Kryvinska, N., Alsubai, S., Krichen, M., Hejaili, A. A., & Sampedro, G. A. (2025) · Scientific Reports · doi:10.1038/s41598-025-10086-y · Cited by 46
A Survey of Multi-Access Edge Computing and Vehicular Networking
Hou, L., Gregory, M. A., & Li, S. (2022) · IEEE Access · doi:10.1109/access.2022.3224032 · Cited by 46
“DT can accurately replicate the physical object in the digital domain, and the virtual twin can constantly interact and synchronously evolve with the physical entity throughout the whole life cycle [114].”
BackgroundMügge, J., Hahn, I. R., Riedelsheimer, T., Chatzis, J., & Boes, J. (2023) · Procedia CIRP · doi:10.1016/j.procir.2023.03.150 · Cited by 43
Digital Twin Smart Water Conservancy: Status, Challenges, and Prospects
Li, W., Ma, Z., Li, J., Li, Q., Li, Y., & Yang, J. (2024) · Water · doi:10.3390/w16142038 · Cited by 49
Agricultural digital twin for smart farming: A review
Subeesh, A., & Chauhan, N. (2025) · Green Technologies and Sustainability · doi:10.1016/j.grets.2025.100299 · Cited by 63
The AI-mediated intimacy economy: a paradigm shift in digital interactions
Bozdağ, A. A. (2025) · AI & SOCIETY · doi:10.1007/s00146-024-02132-6 · Cited by 42
“Digital twins, ranging from basic models capturing essential data to advanced versions replicating complete product data, use machine learning to adjust to environmental and user changes autonomously (Singh et al. 2021).”
Singh, M., Kapukotuwa, J., Gouveia, E. L., Fuenmayor, E., Qiao, Y.-S., Murry, N., & Devine, D. (2024) · Italian National Conference on Sensors · doi:10.3390/s24175680 · Cited by 51
“Overall, the integration of DTs into manufacturing workflows promises to drive significant improvements in productivity, efficiency, and flexibility, setting the stage for the next generation of smart manufacturing solutions.”
BackgroundSelf-citationDigital twins: cornerstone to circular economy and sustainability goals
Ali, Z. A., Zain, M., Hasan, R., Pathan, M. S., AlSalman, H., & Almisned, F. (2025) · Environment Development and Sustainability · doi:10.1007/s10668-025-06221-4 · Cited by 64
Singh, D., Akram, S. V., Singh, R., Gehlot, A., Buddhi, D., Priyadarshi, N., Sharma, G., & Bokoro, P. N. (2022) · Electronics · doi:10.3390/electronics11172700 · Cited by 42
Marketing Strategies 4.0: Recent Trends and Technologies in Marketing
Kaur, R., Singh, R., Gehlot, A., Priyadarshi, N., & Twala, B. (2022) · Sustainability · doi:10.3390/su142416356 · Cited by 76
“REVIEW However, considering that marketing operations primarily leverage blockchain as a widely used database, the data entered into such databases must be of a high standard, because a fault in the source will lead to disruption in the whole network [83].”
BackgroundUsing Digital Twin in a Shipbuilding Project
Kunkera, Z., Opetuk, T., Hadžić, N., & Tošanović, N. (2022) · Applied Sciences · doi:10.3390/app122412721 · Cited by 36
Digital twin challenges in biodiversity modelling
Trantas, A., Plug, R., Pileggi, P., & Lazovik, E. (2023) · Ecological Informatics · doi:10.1016/j.ecoinf.2023.102357 · Cited by 43
A Digital Twin of Charging Stations for Fleets of Electric Vehicles
Francisco, A. M. B., Monteiro, J., & Cardoso, P. J. S. (2023) · IEEE Access · doi:10.1109/access.2023.3330833 · Cited by 41
“Overall, a DT helps to further improve efficiency, reduce costs, and reduce payback periods [9], [10].”
BackgroundDigital Twins for Water Distribution Systems
Berglund, E. Z., Shafiee, M. E., Xing, L., & Wen, J. (2023) · Journal of Water Resources Planning and Management · doi:10.1061/jwrmd5.wreng-5786 · Cited by 41
From modeling and simulation to Digital Twin: evolution or revolution?
Ali, Z., Biglari, R., Denil, J., Mertens, J., Poursoltan, M., & Traoré, M. (2024) · International Conference on Advances in System Simulation · doi:10.1177/00375497241234680 · Cited by 32
“110 Some real-time aspects require investigation in the DT concept: The availability of quantitative data and advanced analytics in real-time via DT enables better-informed and faster decision-making.”
Jiang, C., & Chen, N.-Z. (2025) · Marine Structures · doi:10.1016/j.marstruc.2025.103813 · Cited by 45
Appuhamilage, G. D. K. K., Hussain, M., Zaman, M., & Khan, W. A. (2025) · npj Digital Medicine · doi:10.1038/s41746-025-01738-4 · Cited by 40
“As their potential became evident, digital twins gainedattentionfromothersectors,becomingastrategictechnologyforkey businessplayers 14 .”
Vyskočil, J., Douda, P., Novák, P., & Wally, B. (2023) · Sustainability · doi:10.3390/su15076251 · Cited by 33
“With this architecture, the planner and scheduler have direct access to the current production system state equipped with the continuous synchronization between the digital twin [51,76] and the real production system.”
BackgroundKim, S., Lee, H., Lim, J., Park, J., & Lee, Y. M. (2024) · ACS Energy Letters · doi:10.1021/acsenergylett.4c01931 · Cited by 39
Digital Twin Development for the Airspace of the Future
Souanef, T., Al–Rubaye, S., Tsourdos, A., Ayo, S., & Panagiotakopoulos, D. (2023) · Drones · doi:10.3390/drones7070484 · Cited by 38
Mutual information-enhanced digital twin promotes vision-guided robotic grasping
Hu, F.-W. (2022) · Advanced Engineering Informatics · doi:10.1016/j.aei.2022.101562 · Cited by 36
Pretel, E., Moya, A., Navarro, E., López-Jaquero, V., & González, P. (2024) · Information and Software Technology · doi:10.1016/j.infsof.2024.107503 · Cited by 35
Fan, H., Zhang, H., Ma, C., Wu, T., Fuh, J. Y. H., & Li, B. (2024) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2024.06.007 · Cited by 42
Agelli, M., Corona, N., Maggio, F., & Moi, P. V. (2024) · Machines · doi:10.3390/machines12110750 · Cited by 37
Lehmann, J., Lober, A., Häußermann, T. M., Rache, A., Ollinger, L., Baumgärtel, H., & Reichwald, J. (2023) · Machines · doi:10.3390/machines11050504 · Cited by 43
Advanced manufacturing and digital twin technology for nuclear energy*
Mondal, K., Martinez, O. A., & Jain, P. (2024) · Frontiers in Energy Research · doi:10.3389/fenrg.2024.1339836 · Cited by 44
Comparative Study of Digital Twin Developed in Unity and Gazebo
Singh, M., Kapukotuwa, J., Gouveia, E. L. S., Fuenmayor, E. A., Qiao, Y., Murray, N., & Devine, D. M. (2025) · Electronics · doi:10.3390/electronics14020276 · Cited by 36
Self-citationDigital Twin Cognition: AI-Biomarker Integration in Biomimetic Neuropsychology
Gkintoni, E., & Halkiopoulos, C. (2025) · Biomimetics · doi:10.3390/biomimetics10100640 · Cited by 46
A systematic review of digital twins for electric vehicles
Verma, S., Sharma, A., Tran, B. Q., & Alahakoon, D. (2024) · Journal of Traffic and Transportation Engineering · doi:10.1016/j.jtte.2024.04.004 · Cited by 44
Akhavan, M., Alivirdi, M., Jamalpour, A., Kheradranjbar, M., Mafi, A., Jamalpour, R., & Ravanshadnia, M. (2025) · Buildings · doi:10.3390/buildings15091491 · Cited by 35
Loaiza, J. H., & Cloutier, R. J. (2022) · Systems · doi:10.3390/systems10020022 · Cited by 38
Digital twin in hydrocarbon industry
Sircar, A., Nair, A., Bist, N., & Yadav, K. (2022) · Petroleum Research · doi:10.1016/j.ptlrs.2022.04.001 · Cited by 38
A Review on Recent Trends and Applications of IoT in Additive Manufacturing
Chigilipalli, B. K., Karri, T., Chetti, S. N., Bhiogade, G., Kottala, R. K., & Cheepu, M. (2023) · Applied System Innovation · doi:10.3390/asi6020050 · Cited by 37
“The conceptual model that was suggested by Grieves in 2006 was originally referred to as the “Mirrored Spaces Model,” but in 2006, it was renamed the “Information Mirroring Model” [33,35,38].”
BackgroundMethodInfluentialDigital Twin Test-Bench Performance for Marine Diesel Engine Applications
Мinchev, D., Варбанець, Р. А., Shumylo, O., Zalozh, V., Александровська, Н. І., Bratchenko, P., & Truong, T. H. (2023) · Polish Maritime Research · doi:10.2478/pomr-2023-0061 · Cited by 34
Application of Digital Twin in Electric Vehicle Powertrain: A Review
Li, X., Niu, W., & Tian, H. (2024) · World Electric Vehicle Journal · doi:10.3390/wevj15050208 · Cited by 36
Rahman, M. A., Islam, M. R., Hossain, M. J., Raña, M. S., Hossain, M. J., & Gray, E. M. (2024) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2024.108785 · Cited by 34
Home monitoring in asthma: towards digital twins
Drummond, D., Roukema, J., & Pijnenburg, M. W. H. (2023) · Current Opinion in Pulmonary Medicine · doi:10.1097/mcp.0000000000000963 · Cited by 34
The Role of Multi-Agents in Digital Twin Implementation: Short Survey
Kalyani, Y., & Collier, R. (2024) · ACM Computing Surveys · doi:10.1145/3697350 · Cited by 33
“DT merges the physical and digital worlds to create dynamic [43, 48], self-evolving models [43] that reflect real-life entities ranging from individual components to complex systems.”
Research streams and open challenges in the metaverse
Carrión, C. (2023) · The Journal of Supercomputing · doi:10.1007/s11227-023-05544-1 · Cited by 34
“While the concept 1 3 Research streams and open challenges in the metaverse of DT has been in existence for decades, its impact has become increasingly significant in recent years [33].”
Shen, Z., Xu, W., Li, W., Shi, Y., & Gao, F. (2023) · Solar Energy · doi:10.1016/j.solener.2023.01.007 · Cited by 32
Shah, I. A., Sial, Q., Jhanjhi, N. Z., & Gaur, L. (2022) · Advances in medical technologies and clinical practice book series · doi:10.4018/978-1-6684-5925-6.ch007 · Cited by 32
Manickam, S., Yarlagadda, L., Gopalan, S. P., & Chowdhary, C. L. (2023) · IEEE Access · doi:10.1109/access.2023.3338530 · Cited by 35
“It is worth noting that the definition and categorization of Digital Twins in their current state are contingent upon their application areas [29] and their corresponding integration levels.”
BackgroundIyer, A. A., & Umadevi, K. S. (2025) · Scientific Reports · doi:10.1038/s41598-025-08824-3 · Cited by 32
Maddahi, Y., & Chen, S.-Q. (2022) · Virtual Worlds · doi:10.3390/virtualworlds1010003 · Cited by 17
Potentials of digital twin system for analyzing travel behavior decisions
Aghaabbasi, M., & Sabri, S. (2024) · Travel Behaviour and Society · doi:10.1016/j.tbs.2024.100902 · Cited by 31
Ahmmed, M. S., Khan, L., Mahmood, M. A., & Liou, F. (2025) · Machines · doi:10.3390/machines13080691 · Cited by 35
“Digital Twin (DT) technology is emerging as a key pillar for achieving several benefits in the era of Industry 4.0, as sectors such as manufacturing undergo digital transformation [1,32].”
InfluentialNovák, P., & Vyskočil, J. (2022) · Processes · doi:10.3390/pr10020404 · Cited by 33
Supersystem digital twin-driven framework for new product conceptual design
Haynes, P., & Yang, S. L. (2023) · Advanced Engineering Informatics · doi:10.1016/j.aei.2023.102149 · Cited by 30
Metcalfe, B., Boshuizen, H., Bulens, J., & Koehorst, J. (2023) · F1000Research · doi:10.12688/f1000research.137262.1 · Cited by 29
A digital twin model for evidence-based clinical decision support in multiple myeloma treatment
Grieb, N., Schmierer, L., Kim, H. U., Strobel, S., Schulz, C., Meschke, T., Kubasch, A. S., Brioli, A., Platzbecker, U., Neumuth, T., et al. (2023) · Frontiers in Digital Health · doi:10.3389/fdgth.2023.1324453 · Cited by 32
“The de fi nition of a DT can feature the requirement of data exchange in real time between the physical entity (patient) and the virtual copy (51).”
BackgroundBuilding on Digital Twin: Overcoming Barriers and Unlocking Success in the Construction Industry
Zhu, H., Hwang, B., Tan, Y. Z., & Wei, F. (2024) · Journal of Construction Engineering and Management · doi:10.1061/jcemd4.coeng-13991 · Cited by 30
Wilson, R., Mercier, P. H. J., & Navarra, A. (2022) · Mining · doi:10.3390/mining2010008 · Cited by 29
Singh, R., Gehlot, A., Akram, S. V., Thakur, A. K., Gupta, L. R., Priyadarshi, N., & Twala, B. (2024) · Sustainable Engineering and Innovation · doi:10.37868/sei.v6i1.id208 · Cited by 33
“It is an interconnected accumulation of critical digital artifacts such as operation data, engineering data, and behavior characterizations that can be obtained via numerous simulation models [47], [48].”
BackgroundThe Role of the IoT and Digital Twin in the Healthcare Digitalization Process
Shah, I. A., Sial, Q., Jhanjhi, N. Z., & Gaur, L. (2022) · Advances in medical technologies and clinical practice book series · doi:10.4018/978-1-6684-5925-6.ch002 · Cited by 29
A Review of Digital Twinning for Rotating Machinery
Inturi, V., Ghosh, B., Sabareesh, G. R., & Pakrashi, V. (2024) · Sensors · doi:10.3390/s24155002 · Cited by 33
“This lowers development costs and time to market and prevents material waste [27].”
BackgroundA Digital Twin of the Trondheim Fjord for Environmental Monitoring—A Pilot Case
Vasilijević, A., Brönner, U., Dunn, M., García-Valle, G., Fabrini, J., Stevenson-Jones, R., Bye, B. L., Mayer, I. S., Berre, A. J., Ludvigsen, M., et al. (2024) · Journal of Marine Science and Engineering · doi:10.3390/jmse12091530 · Cited by 29
Review of Applications of Digital Twins and Industry 4.0 for Machining
da Silva, L. R. R., Pimenov, D. Y., da Silva, R. B., Erçetin, A., & Giasin, K. (2025) · Journal of Manufacturing and Materials Processing · doi:10.3390/jmmp9070211 · Cited by 34
SIGNED: Smart cIty diGital twiN vErifiable Data Framework
Pervez, Z., Khan, Z., Abbasi, A. G., & Soomro, K. (2023) · IEEE Access · doi:10.1109/access.2023.3260621 · Cited by 28
“predictive analyses to assess future behaviour [1], [2].”
BackgroundPivotal role of digital twins in the metaverse: A review
Sai, S., Sharma, P., Gaur, A., & Chamola, V. (2024) · Digital Communications and Networks · doi:10.1016/j.dcan.2024.12.003 · Cited by 37
Text mining techniques for the management of predictive maintenance
Nota, G., Postiglione, A., & Carvello, R. (2022) · Procedia Computer Science · doi:10.1016/j.procs.2022.01.276 · Cited by 33
Andriopoulos, N., Plakas, K. A., Mountzouris, C., Gialelis, J., Birbas, A. N., Karatzas, S. K., & Papalexopoulos, A. D. (2023) · Applied Sciences · doi:10.3390/app13031798 · Cited by 27
Sigawi, T., & Ilan, Y. (2023) · Biomimetics · doi:10.3390/biomimetics8040359 · Cited by 27
“The digital twin platform is divided into three linkage stages [24,33,34].”
BackgroundKim, M.-G., & Bartos, M. (2023) · Environmental Modelling & Software · doi:10.1016/j.envsoft.2023.105868 · Cited by 25
Liu, Y.-J., Du, H., Xu, X., Zhang, R., Feng, G., Cao, B., Niyato, D. T., Kim, D. I., Jamalipour, A., Letaief, K. B., et al. (2025) · IEEE Transactions on Cognitive Communications and Networking · doi:10.1109/tccn.2025.3558992 · Cited by 29
“1) Digital Twin: Digital twins create digital models of physical objects, systems or procedures, mirroring their current status and dynamics synchronously [136].”
Omar, O. (2025) · Sustainability · doi:10.3390/su17156670 · Cited by 32
Lehmann, J., Schorz, S., Rache, A., Häußermann, T., Raedle, M., & Reichwald, J. (2023) · Italian National Conference on Sensors · doi:10.3390/s23010468 · Cited by 25
“Just by identifying and focusing on the domain-specific challenges this lack of utilizing the opportunities can be tackled [8,27].”
BackgroundIntelligent Retrofitting Paradigm for Conventional Machines towards the Digital Triplet Hierarchy
Alimam, H., Mazzuto, G., Ortenzi, M., Ciarapica, F., & Bevilacqua, M. (2023) · Sustainability · doi:10.3390/su15021441 · Cited by 21
Properties and Characteristics of Digital Twins: Review of Industrial Definitions
Schweiger, L., & Barth, L. (2023) · SN Computer Science · doi:10.1007/s42979-023-01937-4 · Cited by 28
Industrial Revolutions and Automation: Tracing Economic and Social Transformations of Manufacturing
Szeszák, B. M., Kerékjártó, I. G., Soltész, L., & Galambos, P. (2025) · Societies · doi:10.3390/soc15040088 · Cited by 37
Stach, C. (2023) · Future Internet · doi:10.3390/fi15020071 · Cited by 37
“Furthermore, all machines are connected to data processing infrastructures, which continuously analyze the measured data to monitor the manufacturing process and, if necessary, intervene to optimize it [5].”
BackgroundDigital Twin Applications in Manufacturing Industry: A Case Study from a German Multi-National
Wynn, M. G., & Irizar, J. (2023) · Future Internet · doi:10.3390/fi15090282 · Cited by 24
From BIM to digital twin. IOT data integration in asset management platform
Biagini, C., Bongini, A., & Marzi, L. (2024) · Journal of Information Technology in Construction · doi:10.36680/j.itcon.2024.049 · Cited by 24
“This includes planning and cost estimation for asset management, predicting operational issues, enhancing maintenance activities, increasing information accessibility and security, reducing waste, and improving documentation (Singh et al., 2021).”
Maksimović, M., Jokić, S., & Boskovic, M. C. (2025) · Process Integration and Optimization for Sustainability · doi:10.1007/s41660-024-00478-4 · Cited by 26
“The use of DTs and the Metaverse represents some of the newest technologies that have captured considerable interest in SG modeling and the creation of VPPs. Virtual plant optimization uses DTs and Metaverse technologies to simulate and optimize factory designs (Singh et al. 2021).”
InfluentialRaza, S. M., Minerva, R., Crespi, N., Alvi, M., Herath, M., & Dutta, H. (2025) · Computer Communications · doi:10.1016/j.comcom.2025.108144 · Cited by 27
Bae, C.-H., Choi, E.-T., & Lee, S. (2025) · IEEE Access · doi:10.1109/access.2025.3601615 · Cited by 40
“The digital twin can generate various values, such as reducing development time, lowering development costs, optimizing operations, enhancing stake-holder communication, and creating diverse values through information technology convergence [14], [15].”
AI-Driven Digital Twins in Industrialized Offsite Construction: A Systematic Review
Najafzadeh, M., & Yeganeh, A. J. (2025) · Buildings · doi:10.3390/buildings15172997 · Cited by 24
A Digital Twin for Grassland Management
Purcell, W., Klipic, A., & Neubauer, T. (2022) · International Conference on Electrical, Computer and Energy Technologies (ICECET) · doi:10.1109/icecet55527.2022.9873446 · Cited by 24
“First introduced in 2003 by Dr. Michael Grieves, initially the concept of virtual replicates was relatively innovative [9], [10].”
BackgroundLoaiza, J. H., Cloutier, R. J., & Lippert, K. J. (2023) · Systems · doi:10.3390/systems11010041 · Cited by 28
TOWARDS BIM-GIS INTEGRATION FOR ROAD INTELLIGENT MANAGEMENT SYSTEM
Cepa, J. J., Pavón, R. M., Alberti, M. G., & Caramés, P. (2023) · Journal of Civil Engineering and Management · doi:10.3846/jcem.2023.19514 · Cited by 26
Digital twins for internal combustion engines: A brief review
Trần, V. D., Sharma, P., & Nguyen, L. H. (2023) · Journal of Emerging Science and Engineering · doi:10.61435/jese.2023.5 · Cited by 23
Kantaros, A., & Ganetsos, T. (2024) · American Journal of Engineering and Applied Sciences · doi:10.3844/ajeassp.2024.1.22 · Cited by 19
“This rеmotе monitoring capability not only minimizеs thе nееd for on-sitе inspеctions but also rеducеs maintеnancе costs, еxtеnds еquipmеnt lifеspan and еnhancеs thе ovеrall rеliability of critical manufacturing infrastructurе (Singh et al ., 2021).”
Alimamy, S., & Jung, T. H. (2024) · Journal of Service Research · doi:10.1177/10946705241265753 · Cited by 30
“On the external side of the spectrum, AR and Mirror Worlds exist; the latter has given rise to the concept of digital twin — a passing evolution from Mirror Worlds into digital representations of physical objects (Singh et al. 2021).”
Predictive Analysis of a Building’s Power Consumption Based on Digital Twin Platforms
Han, F., Du, F., Jiao, S., & Zou, K. (2024) · Energies · doi:10.3390/en17153692 · Cited by 26
Maïzi, Y., Arcand, A., & Bendavid, Y. (2024) · Internet of Things · doi:10.1016/j.iot.2024.101379 · Cited by 23
Sustainable Intelligent Transportation Systems via Digital Twins: A Contextualized Survey
Martínez, V. M. G., Campelo, D. R. D. S., & Ribeiro, M. R. N. (2025) · IEEE Open Journal of Intelligent Transportation Systems · doi:10.1109/ojits.2025.3553696 · Cited by 24
“Readers are referred to surveys that deal with foundation concepts of DTs [15], [16], [17], [18], [19], [20], [21], [22]; industry verticals [23], [24], [25], [26] and also in Industry 4.0 manufacturing models [27]; civil engineering [28], [29], [30], [31], [32], [33]; agriculture [34], [35], [36];…”
InfluentialThe Future of Digital Twin Research and Development
Bossuyt, D. L. V., Allaire, D., Bickford, J. F., Bozada, T. A., Chen, W., Cutitta, R. P., Cuzner, R. M., Fletcher, K. M., Giachetti, R. E., Hale, B., et al. (2025) · Journal of Computing and Information Science in Engineering · doi:10.1115/1.4068082 · Cited by 27
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
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.
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