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
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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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Self-citationDeep learning for smart manufacturing: Methods and applications
Wang, J., Ma, Y., Zhang, L., Gao, R. X., & Wu, D. (2018) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2018.01.003 · Cited by 1,740
Digital twin and big data towards smart manufacturing and Industry 4.0: 360 degree comparison
Qi, Q., & Tao, F. (2018) · IEEE Access · doi:10.1109/access.2018.2793265 · Cited by 1,716
Self-citationA Review of the Roles of Digital Twin in CPS-based Production Systems
Negri, E., Fumagalli, L., & Macchi, M. (2017) · Procedia Manufacturing · doi:10.1016/j.promfg.2017.07.198 · Cited by 1,669
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Self-citationAbout 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
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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
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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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