The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Make more digital twins
Open accessAbstract
Virtual models boost smart manufacturing by simulating decisions and optimization, from design to operations, explain Fei Tao and Qinglin Qi. Virtual models boost smart manufacturing by simulating decisions and optimization, from design to operations, explain Fei Tao and Qinglin Qi.
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“The fragmentation of data ownership, disparate data types, and challenges related to patenting and proprietary knowledge further limit accessibility and integration [133].”
From Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0 (2025) · cites this paper as [133]
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“Synthetic datasets are artificially generated to reflect the characteristics of real patient data and can be used to train and test models without exposing sensitive information [80].”
From Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22. (2025) · cites this paper as [80]
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Citations
Cites
Smart manufacturing must embrace big data
Kusiak, A. (2017) · Nature · doi:10.1038/544023a · Cited by 636
Digital Twin Driven Smart Manufacturing
Tao, F., Zhang, M., & Nee, A. Y. C. (2019) · Elsevier eBooks · doi:10.1016/c2018-0-02206-9 · Cited by 284
Research works printed but not linked: 1
- Pettey, C. ‘Prepare for the impact of digital twins’ (2017). Gartner report available at https://go.nature.com/2krzbjd
Cited by
Sorted by citations
Enabling technologies and tools for digital twin
Qi, Q., Tao, F., Hu, T., Anwer, N., Liu, A., Wei, Y., Wang, L., & Nee, A. Y. C. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2019.10.001 · Cited by 1,579
Self-citationTao, 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
Digital Twins: State of the art theory and practice, challenges, and open research questions
Sharma, A., Kosasih, E., Zhang, J., Brintrup, A., & Calinescu, A. (2022) · Journal of Industrial Information Integration · doi:10.1016/j.jii.2022.100383 · Cited by 587
Digital twins to personalize medicine
on behalf of the Swedish Digital Twin Consortium, Björnsson, B., Borrebaeck, C., Elander, N., Gasslander, T., Gawel, D. R., Gustafsson, M., Jörnsten, R., Lee, E. J., Li, X., et al. (2020) · Genome Medicine · doi:10.1186/s13073-019-0701-3 · Cited by 566
Fusing Blockchain and AI With Metaverse: A Survey
Yang, Q., Zhao, Y., Huang, H., Xiong, Z., Kang, J., & Zheng, Z. (2022) · IEEE Open Journal of the Computer Society · doi:10.1109/ojcs.2022.3188249 · Cited by 576
Metadata
- Authors
- Tao, F., & Qi, Q.
- Affiliations
- Beihang University (CN)
- Corresponding author
- Tao, Fei
- Qi, Qinglin
- ORCID
- Venue
- Nature
- Published
- 2019-09-25
- Volume
- 573
- Issue
- 7775
- Pages
- 490-491
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2976301483
- Cited by
- 799
- References
- 2
- Citations by year
- 2026: 108 · 2025: 174 · 2024: 165 · 2023: 132 · 2022: 112 · 2021: 73 · 2020: 30 · 2019: 5
- FWCI
- 40.59
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature (publishedVersion, other-oa)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Manufacturing Process and Optimization
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Flexible and Reconfigurable Manufacturing Systems
- Keywords
- digital twin, virtual models, smart manufacturing, decision simulation, optimization, product design, manufacturing operations
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