The DOI matches its Crossref record, with a small difference in title or year; 51 of the 52 references it cites were found in a registry or an index.
Enabling technologies and tools for digital twin
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In the citing paper
“Furthermore, DTs improve business performance by streamlining operations and accelerating the achievement of value and competitive advantages [8].”
From Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0 (2025) · cites this paper as [8]
In the citing paper
“Due to the different formats, standards and protocols, current tools are not integrated and simultaneously used for a specific objective [7]”
From Digital Twin Technology Challenges and Applications: A Comprehensive Review (2022) · cites this paper as [7]
Citations
Cites
Digital Twin in Industry: State-of-the-Art
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Self-citationDigital Twin in manufacturing: A categorical literature review and classification
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Self-citationThe Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles
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Data-driven smart manufacturing
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Self-citationDeep learning for smart manufacturing: Methods and applications
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Digital twin and big data towards smart manufacturing and Industry 4.0: 360 degree comparison
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Self-citationA Review of the Roles of Digital Twin in CPS-based Production Systems
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Self-citationAbout The Importance of Autonomy and Digital Twins for the Future of Manufacturing
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Tao, F., & Zhang, M. (2017) · IEEE Access · doi:10.1109/access.2017.2756069 · Cited by 1,397
Self-citationShaping the digital twin for design and production engineering
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Tao, F., Zhang, M., Liu, Y., & Nee, A. Y. C. (2018) · CIRP Annals · doi:10.1016/j.cirp.2018.04.055 · Cited by 1,000
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Self-citationToward 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
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 Service towards Smart Manufacturing
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Self-citationDigital Twin Data Modeling with AutomationML and a Communication Methodology for Data Exchange
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Tao, F., & Qi, Q. (2017) · IEEE Transactions on Systems Man and Cybernetics Systems · doi:10.1109/tsmc.2017.2723764 · Cited by 434
Self-citationThe role of data fusion in predictive maintenance using digital twin
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The digital twin of an industrial production line within the industry 4.0 concept
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Modular based flexible digital twin for factory design
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Manufacturing Service Management in Cloud Manufacturing: Overview and Future Research Directions
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Self-citationDigital Twin of a Cutting Tool
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Self-citationCombined strength of holons, agents and function blocks in cyber-physical systems
Wang, L., & Haghighi, A. (2016) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2016.05.002 · Cited by 121
Self-citationStructural Health Management of Damaged Aircraft Structures Using Digital Twin Concept
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A simulation-based approach for plant layout design and production planning
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Fleet Monitoring and Diagnostics Framework Based on Digital Twin of Aero-Engines
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Cloud manufacturing paradigm with ubiquitous robotic system for product customization
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Self-citationThe Development and use of a Digital Twin Model for Tire Touchdown Health Monitoring
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Self-citationDynamic resource allocation optimization for digital twin-driven smart shopfloor
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Independent Verification and Validation of an Industrial Simulation Model
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A review of designing machine tool for leanness
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Optimized throughput improvement of assembly flow line with digital twin online analytics
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Research works printed but not linked: 3
- Tao, 2017, Digital twin workshop: a new paradigm for future workshop, Comput Integr Manuf Syst, 23, 1
- Tao, 2019, Five-dimension digital twin model and its ten applications, Comput Integr Manuf Syst, 25, 1
- Zhang, 2019, A simulation-based approach for plant layout design and production planning, J Ambient Intell Humaniz Comput, 10, 1217, 10.1007/s12652-018-0687-5 · DOI
Cited by
Sorted by citations
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
Tao, F., Xiao, B., Qi, Q., Cheng, J., & Ji, P. (2022) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2022.06.015 · Cited by 1,255
Self-citationDigital Twins: A Survey on Enabling Technologies, Challenges, Trends and Future Prospects
Mihai, S., Yaqoob, M., Hưng, Đ. V., Davis, W., Towakel, P., Raza, M., Karamanoglu, M., Barn, B. S., Shetve, D., Prasad, R. V., et al. (2022) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2022.3208773 · Cited by 1,195
Digital Twin Technology Challenges and Applications: A Comprehensive Review
Botín-Sanabria, D. M., Mihaita, A.-S., Peimbert-García, R. E., Ramírez-Moreno, M. A., Ramírez-Mendoza, R. A., & Lozoya-Santos, J. D. J. (2022) · Remote Sensing · doi:10.3390/rs14061335 · Cited by 878
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
Metadata
- Authors
- Qi, Q., Tao, F., Hu, T., Anwer, N., Liu, A., Wei, Y., Wang, L., & Nee, A. Y. C.
- Affiliations
- Beihang University (CN)
- Shandong University (CN)
- Université Paris-Sud (FR)
- UNSW Sydney (AU)
- KTH Royal Institute of Technology (SE)
- National University of Singapore (SG)
- Corresponding author
- Tao, Fei
- Venue
- Journal of Manufacturing Systems
- Publisher
- Elsevier BV
- Published
- 2021-01
- Volume
- 58
- Pages
- 3-21
- ISSN
- 0278-6125 (ISSN-L)
- OpenAlex
- W2982689699
- Cited by
- 1,579
- References
- 52
- Citations by year
- 2026: 221 · 2025: 299 · 2024: 351 · 2023: 318 · 2022: 205 · 2021: 122
- FWCI
- 72.15
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Manufacturing Systems (publishedVersion)
- HAL (submittedVersion)
- Funders
- National Basic Research Program of China
- National Natural Science Foundation of China
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Applied Advanced Technologies
- Physical Sciences › Engineering › Building and Construction › BIM and Construction Integration
- Keywords
- digital twin, enabling technologies, sensor data, data integration, digital twin implementation
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