The DOI matches its Crossref record; 144 of the 144 references it cites were found in a registry or an index.
Digital twin paradigm: A systematic literature review
Open accessOverview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Distributed Representations of Words and Phrases and their Compositionality
Mikolov, T., Sutskever, I., Chen, K., Corrado, G., & Dean, J. (2013) · arXiv · doi:10.48550/arxiv.1310.4546 · Cited by 24,533
The Internet of Things: A survey
Atzori, L., Iera, A., & Morabito, G. (2010) · Computer Networks · doi:10.1016/j.comnet.2010.05.010 · Cited by 15,613
Mining association rules between sets of items in large databases
Agrawal, R., Imieliński, T., & Swami, A. (1993) · Proceedings of the 1993 ACM SIGMOD international conference on Management of data · doi:10.1145/170035.170072 · Cited by 14,907
Internet of Things (IoT): A vision, architectural elements, and future directions
Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013) · Future Generation Computer Systems · doi:10.1016/j.future.2013.01.010 · Cited by 12,293
Simulation Modeling and Analysis.
Schervish, M. J., Law, A. M., & Kelton, W. D. (1983) · Journal of the American Statistical Association · doi:10.2307/2288169 · Cited by 8,697
Survey of Clustering Algorithms
Xu, R., & WunschII, D. (2005) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2005.845141 · Cited by 6,197
Internet of Things in industries: A survey
Xu, L. D., He, W., & Li, S. (2014) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2014.2300753 · Cited by 5,172 · cited 1×
“This layer connects all components together for sharing data and information with other connected components (Da Xu et al., 2014).”
BackgroundA Cyber-Physical Systems architecture for Industry 4.0-based manufacturing systems
Lee, J., Bagheri, B., & Kao, H.-A. (2015) · Manufacturing Letters · doi:10.1016/j.mfglet.2014.12.001 · Cited by 5,113
Simulation modeling and analysis
(1999) · Journal of Manufacturing Systems · doi:10.1016/s0278-6125(99)90119-x · Cited by 3,833
Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems
Grieves, M., & Vickers, J. (2017) · Transdisciplinary Perspectives on Complex Systems · doi:10.1007/978-3-319-38756-7_4 · Cited by 3,727 · cited 4×
“As the concept was emerging out of the field of Product life cycle management (PLM), (Grieves and Vickers, 2017) referred to the connection between real space and virtual space over all phases of the product life cycle presenting all the elements of the Digital Twin: real space, virtual space, the…”
BackgroundInfluential
Cited by
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
Applications of Digital Twin across Industries: A Review
Singh, M., Srivastava, R., Fuenmayor, E., Kuts, V., Qiao, Y., Murray, N., & Devine, D. (2022) · Applied Sciences · doi:10.3390/app12115727 · Cited by 355
Toward the Next Generation of Digitalization in Agriculture Based on Digital Twin Paradigm
Nasirahmadi, A., & Hensel, O. (2022) · Sensors · doi:10.3390/s22020498 · Cited by 304
Understanding Physics-Informed Neural Networks: Techniques, Applications, Trends, and Challenges
Farea, A., Yli-Harja, O., & Emmert-Streib, F. (2024) · AI · doi:10.3390/ai5030074 · Cited by 259
A survey of Digital Twin techniques in smart manufacturing and management of energy applications
Wang, Y., Kang, X., & Chen, Z. (2022) · Green Energy and Intelligent Transportation · doi:10.1016/j.geits.2022.100014 · Cited by 147
Metadata
- Authors
- Semeraro, C., Lezoche, M., Panetto, H., & Dassisti, M.
- Venue
- Computers in Industry
- Publisher
- Elsevier BV
- Published
- 2021-09
- Volume
- 130
- Pages
- 103469
- ISSN
- 0166-3615 (ISSN-L)
- OpenAlex
- W3160372581
- Cited by
- 986
- References
- 144
- FWCI
- 14.77
- Type
- journal article
- Language
- en
- Open access
- bronze
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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Digital twin paradigm: A systematic literature review. https://app.cochat.ai/papers/10.1016/j.compind.2021.103469
- The paper
- Semeraro, C., Lezoche, M., Panetto, H., & Dassisti, M. (2021). Digital twin paradigm: A systematic literature review. Computers in Industry. https://doi.org/10.1016/j.compind.2021.103469
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.