The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Experimentable Digital Twins—Streamlining Simulation-Based Systems Engineering for Industry 4.0
Abstract
Digital twins represent real objects or subjects with their data, functions, and communication capabilities in the digital world. As nodes within the internet of things, they enable networking and thus the automation of complex value-added chains. The application of simulation techniques brings digital twins to life and makes them experimentable; digital twins become experimentable digital twins (EDTs). Initially, these EDTs communicate with each other purely in the virtual world. The resulting networks of interacting EDTs model different application scenarios and are simulated in virtual testbeds, providing new foundations for comprehensive simulation-based systems engineering. Its focus is on EDTs, which become more detailed with every single application. Thus, complete digital representations of the respective real assets and their behaviors are created successively. The networking of EDTs with real assets leads to hybrid application scenarios in which EDTs are used in combination with real hardware, thus realizing complex control algorithms, innovative user interfaces, or mental models for intelligent systems.
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Cites
Powell, M. J. D. (1964) · The Computer Journal · doi:10.1093/comjnl/7.2.155 · Cited by 4,632
Cited by
Digital Twin in Industry: State-of-the-Art
Tao, F., Zhang, H., Liu, A., & Nee, A. Y. C. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2873186 · Cited by 4,391
Digital twin: values, challenges and enablers from a modeling perspective
Rasheed, A., San, O., & Kvamsdal, T. (2020) · IEEE Access · doi:10.1109/access.2020.2970143 · Cited by 1,952
Leveraging Digital Twin Technology in Model-Based Systems Engineering
Madni, A. M., Madni, C. C., & Lucero, S. D. (2019) · Systems · doi:10.3390/systems7010007 · Cited by 1,050
Blockchain for AI: review and open research challenges
Salah, K., Rehman, M. H. U., Nizamuddin, N., & Al-Fuqaha, A. (2019) · IEEE Access · doi:10.1109/access.2018.2890507 · Cited by 1,001
Digital Twin Networks: A Survey
Wu, Y., Zhang, K., & Zhang, Y. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2021.3079510 · Cited by 847
Metadata
- Authors
- Schluse, M., Priggemeyer, M., Atorf, L., & Rossmann, J.
- Venue
- IEEE Transactions on Industrial Informatics
- Published
- 2018-04
- Volume
- 14
- Issue
- 4
- Pages
- 1722-1731
- ISSN
- 1551-3203 (ISSN-L)
- 1941-0050
- OpenAlex
- W2785458774
- Cited by
- 524
- References
- 1
- FWCI
- 36.76
- Type
- journal article
- Language
- en
- Open access
- closed
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- Schluse, M., Priggemeyer, M., Atorf, L., & Rossmann, J. (2018). Experimentable Digital Twins—Streamlining Simulation-Based Systems Engineering for Industry 4.0. IEEE Transactions on Industrial Informatics. https://doi.org/10.1109/tii.2018.2804917
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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