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Digital Twin—The Simulation Aspect
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“However, NASA had previously employed the same concept during the Apollo program as a”
From Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0 (2025) · cites this paper as [18]
In the citing paper
“It enables the evolution of physical systems into more complex digital environments by integrating software functions, such as drive and sensor connectivity within cyber-physical systems (CPS) [121].”
From Analysis of Digital Twin Applications in Energy Efficiency: A Systematic Review (2025) · cites this paper as [121]
Citations
Cites
About The Importance of Autonomy and Digital Twins for the Future of Manufacturing
Rosen, R., von Wichert, G., Lo, G., & Bettenhausen, K. D. (2015) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2015.06.141 · Cited by 1,474
Self-citationFitzwater, L. M., Torng, Y. T., & Halbert, K. (2011) · doi:10.21236/ada586666 · Cited by 1
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Digital twin-driven product design, manufacturing and service with big data
Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., & Sui, F. (2018) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-017-0233-1 · Cited by 2,920
Characterising the Digital Twin: A systematic literature review
Jones, D., Snider, C., Nassehi, A., Yon, J., & Hicks, B. (2020) · CIRP Journal of Manufacturing Science and Technology · doi:10.1016/j.cirpj.2020.02.002 · Cited by 2,422
Review of digital twin about concepts, technologies, and industrial applications
Liu, M., Fang, S., Dong, H., & Xu, C. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.06.017 · Cited by 2,075
A survey on digital twin: definitions, characteristics, applications, and design implications
Barricelli, B. R., Casiraghi, E., & Fogli, D. (2019) · IEEE Access · doi:10.1109/access.2019.2953499 · Cited by 1,480
Towards a semantic Construction Digital Twin: Directions for future research
Boje, C., Guerriero, A., Kubicki, S., & Rezgui, Y. (2020) · Automation in Construction · doi:10.1016/j.autcon.2020.103179 · Cited by 1,477
Shaping the digital twin for design and production engineering
Schleich, B., Anwer, N., Mathieu, L., & Wartzack, S. (2017) · CIRP Annals · doi:10.1016/j.cirp.2017.04.040 · Cited by 1,305
Digital twin: origin to future
Singh, M., Fuenmayor, E., Hinchy, E., Qiao, Y., Murray, N., & Devine, D. (2021) · Applied System Innovation · doi:10.3390/asi4020036 · Cited by 1,038
Digital twin paradigm: A systematic literature review
Semeraro, C., Lezoche, M., Panetto, H., & Dassisti, M. (2021) · Computers in Industry · doi:10.1016/j.compind.2021.103469 · Cited by 1,129
Digital Twin: Generalization, characterization and implementation
VanDerHorn, E., & Mahadevan, S. (2021) · Decision Support Systems · doi:10.1016/j.dss.2021.113524 · Cited by 808
Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models
Minerva, R., Lee, G. M., & Crespi, N. (2020) · Proceedings of the IEEE · doi:10.1109/jproc.2020.2998530 · Cited by 812
Digital Twin for maintenance: A literature review
Errandonea, I., Beltrán, S., & Arrizabalaga, S. (2020) · Computers in Industry · doi:10.1016/j.compind.2020.103316 · Cited by 819
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Verdouw, C., Tekinerdoğan, B., Beulens, A., & Wolfert, S. (2021) · Agricultural Systems · doi:10.1016/j.agsy.2020.103046 · Cited by 634
A Novel Cloud-Based Framework for the Elderly Healthcare Services Using Digital Twin
Liu, Y., Zhang, L., Yang, Y., Zhou, L., Ren, L., Wang, F., Liu, R., Pang, Z., & Deen, M. J. (2019) · IEEE Access · doi:10.1109/access.2019.2909828 · Cited by 763
Digital twin: benefits, use cases, challenges, and opportunities
Attaran, M., & Celik, B. G. (2023) · Decision Analytics Journal · doi:10.1016/j.dajour.2023.100165 · Cited by 704
Digital Twin as a Service (DTaaS) in Industry 4.0: An Architecture Reference Model
Aheleroff, S., Xu, X. W., Zhong, R. Y., & Lu, Y. (2020) · Advanced Engineering Informatics · doi:10.1016/j.aei.2020.101225 · Cited by 680
Introducing digital twins to agriculture
Pylianidis, C., Osinga, S., & Athanasiadis, I. N. (2021) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2020.105942 · Cited by 753
Toward a Digital Twin for real-time geometry assurance in individualized production
Söderberg, R., Wärmefjord, K., Carlson, J. S., & Lindkvist, L. (2017) · CIRP Annals · doi:10.1016/j.cirp.2017.04.038 · Cited by 543
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An application framework of digital twin and its case study
Zheng, Y., Yang, S., & Cheng, H. (2018) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-018-0911-3 · Cited by 534
Digital twin application in the construction industry: A literature review
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Haag, S., & Anderl, R. (2018) · Manufacturing Letters · doi:10.1016/j.mfglet.2018.02.006 · Cited by 559
Digital Twin for rotating machinery fault diagnosis in smart manufacturing
Wang, J., Ye, L., Gao, R. X., Li, C., & Zhang, L. (2019) · International Journal of Production Research · doi:10.1080/00207543.2018.1552032 · Cited by 552
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A digital twin smart city for citizen feedback
White, G., Zink, A., Codecá, L., & Clarke, S. (2021) · Cities · doi:10.1016/j.cities.2020.103064 · Cited by 548
Digital twin-driven manufacturing cyber-physical system for parallel controlling of smart workshop
Leng, J., Zhang, H., Yan, D., Liu, Q., Chen, X., & Zhang, D. (2019) · Journal of Ambient Intelligence and Humanized Computing · doi:10.1007/s12652-018-0881-5 · Cited by 475
Zhang, H., Liu, Q., Chen, X., Zhang, D., & Leng, J. (2017) · IEEE Access · doi:10.1109/access.2017.2766453 · Cited by 471
Digital twin-driven rapid individualised designing of automated flow-shop manufacturing system
Liu, Q., Zhang, H., Leng, J., & Chen, X. (2019) · International Journal of Production Research · doi:10.1080/00207543.2018.1471243 · Cited by 370
Emerging opportunities and challenges for the future of reservoir computing
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Croatti, A., Gabellini, M., Montagna, S., & Ricci, A. (2020) · Journal of Medical Systems · doi:10.1007/s10916-020-01623-5 · Cited by 356
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Soori, M., Behrooz Arezoo, B., & Dastres, R. (2023) · Sustainable Manufacturing and Service Economics · doi:10.1016/j.smse.2023.100017 · Cited by 411
Shahzad, M., Shafiq, M. T., Douglas, D., & Kassem, M. (2022) · Buildings · doi:10.3390/buildings12020120 · Cited by 356
Zografopoulos, I., Ospina, J., Liu, X., & Konstantinou, C. (2021) · IEEE Access · doi:10.1109/access.2021.3058403 · Cited by 320
Liu, Q., Leng, J., Yan, D., Zhang, D., Wei, L., Yu, A., Zhao, R., Zhang, H., & Chen, X. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.04.012 · Cited by 315
An architecture of an intelligent digital twin in a cyber-physical production system
Ashtari Talkhestani, B., Jung, T., Lindemann, B., Sahlab, N., Jazdi, N., Schloegl, W., & Weyrich, M. (2019) · at - Automatisierungstechnik · doi:10.1515/auto-2019-0039 · Cited by 300
A Survey on Digital Twin for Industrial Internet of Things: Applications, Technologies and Tools
Xu, H., Wu, J., Pan, Q., Guan, X., & Guizani, M. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3297395 · Cited by 304
Framework for a digital twin in manufacturing: Scope and requirements
Shao, G., & Helu, M. (2020) · Manufacturing Letters · doi:10.1016/j.mfglet.2020.04.004 · Cited by 292
Digital twin-based WEEE recycling, recovery and remanufacturing in the background of Industry 4.0
Wang, X. V., & Wang, L. (2019) · International Journal of Production Research · doi:10.1080/00207543.2018.1497819 · Cited by 330
Mohammadi, N., & Taylor, J. E. (2017) · IEEE Symposium Series on Computational Intelligence (SSCI) · doi:10.1109/ssci.2017.8285439 · Cited by 305
Jiang, H., Qin, S., Fu, J., Zhang, J., & Ding, G. (2020) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.05.012 · Cited by 286
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When Internet of Things Meets Metaverse: Convergence of Physical and Cyber Worlds
Li, K., Cui, Y., Li, W., Lv, T., Yuan, X., Li, S., Ni, W., Simsek, M., & Dressler, F. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3232845 · Cited by 299
Data-Driven Aerospace Engineering: Reframing the Industry with Machine Learning
Brunton, S. L., Nathan Kutz, J., Manohar, K., Aravkin, A. Y., Morgansen, K., Klemisch, J., Goebel, N., Buttrick, J., Poskin, J., Blom-Schieber, A. W., et al. (2021) · AIAA Journal · doi:10.2514/1.j060131 · Cited by 270
Data-driven ship digital twin for estimating the speed loss caused by the marine fouling
Coraddu, A., Oneto, L., Baldi, F., Cipollini, F., Atlar, M., & Savio, S. (2019) · Ocean Engineering · doi:10.1016/j.oceaneng.2019.05.045 · Cited by 252
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A systematic review of data science and machine learning applications to the oil and gas industry
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Digital twins: An analysis framework and open issues
Boyes, H. A., & Watson, T. (2022) · Computers in Industry · doi:10.1016/j.compind.2022.103763 · Cited by 241
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Enabling Technologies for Operator 4.0: A Survey
Ruppert, T., Jaskó, S., Holczinger, T., & Abonyi, J. (2018) · Applied Sciences · doi:10.3390/app8091650 · Cited by 236
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Moyne, J. R., Qamsane, Y., Balta, E. C., Kovalenko, I., Faris, J., Barton, K. L., & Tilbury, D. M. (2020) · IEEE Access · doi:10.1109/access.2020.3000437 · Cited by 230
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Qian, C., Liu, X., Ripley, C., Qian, M., Liang, F., & Yu, W. (2022) · Future Internet · doi:10.3390/fi14020064 · Cited by 235
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Schroeder, G. N., Steinmetz, C., Rodrigues, R. N., Henriques, R. V. B., Rettberg, A., & Pereira, C. E. (2021) · Proceedings of the IEEE · doi:10.1109/jproc.2020.3032444 · Cited by 213
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Jin, L., Zhai, X., Wang, K., Zhang, K., Wu, D., Nazir, A., Jiang, J., & Liao, W. (2024) · Materials & Design · doi:10.1016/j.matdes.2024.113086 · Cited by 232
Wagner, C., Grothoff, J., Epple, U., Drath, R., Malakuti, S., Grüner, S., Hoffmeister, M., & Zimermann, P. (2017) · IEEE International Conference on Emerging Technologies and Factory Automation · doi:10.1109/etfa.2017.8247583 · Cited by 178
Design and implementation of a smart infrastructure digital twin
Broo, D. G., Bravo-Haro, M., & Schooling, J. M. (2022) · Automation in Construction · doi:10.1016/j.autcon.2022.104171 · Cited by 217
Havard, V., Jeanne, B., Lacomblez, M., & Baudry, D. (2019) · Production & Manufacturing Research · doi:10.1080/21693277.2019.1660283 · Cited by 183
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Liang, F., Yu, W., Liu, X., GRIFFITH, D. W. T., & Golmie, N. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2963635 · Cited by 209
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Hou, L., Wu, S., Zhang, G. (., Tan, Y., & Wang, X. (2020) · Applied Sciences · doi:10.3390/app11010339 · Cited by 194
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Lattanzi, L., Raffaeli, R., Peruzzini, M., & Pellicciari, M. (2021) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2021.1911003 · Cited by 205
Meraghni, S., Terrissa, L. S., Yue, M., Ma, J., Jemeï, S., & Noureddine Zerhouni, A. (2020) · International Journal of Hydrogen Energy · doi:10.1016/j.ijhydene.2020.10.108 · Cited by 186
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Park, K. T., Nam, Y. W., Lee, H. S., Im, S. J., Noh, S. D., Son, J. Y., & Kim, H. (2019) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2019.1599439 · Cited by 194
Wagner, R., Schleich, B., Haefner, B., Kuhnle, A., Wartzack, S., & Lanza, G. (2019) · Procedia CIRP · doi:10.1016/j.procir.2019.04.219 · Cited by 145
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Damjanović, V., & Behrendt, W. (2019) · International Journal of Computer Integrated Manufacturing · doi:10.1080/0951192x.2019.1599436 · Cited by 165
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Xiong, M., & Wang, H. (2022) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-022-09717-9 · Cited by 187
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Tang, F., Chen, X., Rodrigues, T. K., Zhao, M., & Kato, N. (2022) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2022.3197811 · Cited by 165
Cheng, Y., Zhang, Y., Ji, P., Xu, W., Zhou, Z., & Tao, F. (2018) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-018-2001-2 · Cited by 161
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Eckhart, M., & Ekelhart, A. (2019) · Security and Quality in Cyber-Physical Systems Engineering · doi:10.1007/978-3-030-25312-7_14 · Cited by 158
Recent trends of digital twin technologies in the energy sector: A comprehensive review
Ghenaï, C., Husein, L. A., Nahlawi, M. A., Hamid, A. K., & Bettayeb, M. (2022) · Sustainable Energy Technologies and Assessments · doi:10.1016/j.seta.2022.102837 · Cited by 169
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Lucchi, E. (2023) · Automation in Construction · doi:10.1016/j.autcon.2023.105073 · Cited by 177
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Marmolejo-Saucedo, J. A. (2020) · Mobile Networks and Applications · doi:10.1007/s11036-020-01557-9 · Cited by 166
Longo, F., Nicoletti, L., & Padovano, A. (2019) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2019.01.001 · Cited by 153
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Steindl, G., Stagl, M., Kasper, L., Kästner, W., & Hofmann, R. (2020) · Applied Sciences · doi:10.3390/app10248903 · Cited by 156
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Hribernik, K., Cabri, G., Mandreoli, F., & Mentzas, G. N. (2021) · Computers in Industry · doi:10.1016/j.compind.2021.103508 · Cited by 159
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Autiosalo, J., Vepsäläinen, J., Viitala, R., & Tammi, K. (2019) · IEEE Access · doi:10.1109/access.2019.2950507 · Cited by 151
Vrabič, R., Erkoyuncu, J. A., Butala, P., & Roy, R. (2018) · Procedia Manufacturing · doi:10.1016/j.promfg.2018.10.167 · Cited by 151
Moutis, P. P., & Mousavi, O. A. (2020) · IEEE Transactions on Power Delivery · doi:10.1109/tpwrd.2020.3017355 · Cited by 149
Sayyad, S., Kumar, S., Bongale, A. M., Kamat, P. V., Patil, S., & Kotecha, K. V. (2021) · IEEE Access · doi:10.1109/access.2021.3101284 · Cited by 160
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Albalkhy, W., Karmaoui, D., Ducoulombier, L., Lafhaj, Z., & Linner, T. (2024) · Automation in Construction · doi:10.1016/j.autcon.2024.105368 · Cited by 136
The role of digital twins in lean supply chain management: review and research directions
Guo, D., & Mantravadi, S. (2024) · International Journal of Production Research · doi:10.1080/00207543.2024.2372655 · Cited by 157
The Role of Mobile Technology in Tourism: Patents, Articles, News, and Mobile Tour App Reviews
Kim, D., & Kim, S.-B. (2017) · Sustainability · doi:10.3390/su9112082 · Cited by 145
Brosinsky, C., Westermann, D., & Krebs, R. (2018) · 2018 IEEE International Energy Conference (ENERGYCON) · doi:10.1109/energycon.2018.8398846 · Cited by 165
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Opoku, D.-G. J., Perera, S., Osei‐Kyei, R., Rashidi, M., Famakinwa, T., & Bamdad, K. (2022) · Buildings · doi:10.3390/buildings12020113 · Cited by 134
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Moi, T., Cibicik, A., & Rølvåg, T. (2020) · Engineering Failure Analysis · doi:10.1016/j.engfailanal.2020.104517 · Cited by 118
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Schwarz, C., & Wang, Z. (2022) · IEEE Intelligent Transportation Systems Magazine · doi:10.1109/mits.2021.3129524 · Cited by 133
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Sjarov, M., Lechler, T., Fuchs, J., Brossog, M., Selmaier, A., Faltus, F., Donhauser, T., & Franke, J. E. (2020) · IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) · doi:10.1109/etfa46521.2020.9212089 · Cited by 132
Iliuţă, M.-E., Moisescu, M.-A., Pop, E., Ionita, A.-D., Caramihai, S.-I., & Mitulescu, T.-C. (2024) · Applied Sciences · doi:10.3390/app14135454 · Cited by 134
Metadata
- Authors
- Boschert, S., & Rosen, R.
- Affiliations
- Siemens (Germany) (DE)
- Corresponding author
- Boschert, Stefan
- ORCID
- Boschert, Stefan
- Venue
- Mechatronic Futures
- Publisher
- Springer International Publishing
- Published
- 2016
- Pages
- 59-74
- OpenAlex
- W2482127302
- Cited by
- 1,158
- References
- 2
- Citations by year
- 2026: 78 · 2025: 165 · 2024: 165 · 2023: 175 · 2022: 162 · 2021: 143 · 2020: 128 · 2019: 77 · 2018: 48 · 2017: 13 · 2016: 4
- FWCI
- 107.09
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Springer eBooks (publishedVersion)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Mathematics › Modeling and Simulation › Modeling and Simulation Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Systems Engineering Methodologies and Applications
- Keywords
- digital twin, simulation, modeling and simulation, mechatronic systems, system development, design validation, failure prediction, virtual-physical integration, product life cycle
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