A unified digital twin approach incorporating virtual, physical, and prescriptive analytical components to support adaptive real-time decision-making
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The interlinking mechanisms include IoT devices, data communication protocols, edge and cloud computing, machine learning algorithms, and feedback control systems.
“The interlinking mechanisms include IoT devices, data communication protocols, edge and cloud computing, machine learning algorithms, and feedback control systems [26][27][28].”
From Digital Twins in the IIoT: Current Practices and Future Directions Toward Industry 5.0 (2025) · cites this paper as [26]
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- Authors
- Walton, R. B., Ciarallo, F. W., & Champagne, L. E.
- Affiliations
- Wright-Patterson Air Force Base (US)
- Corresponding author
- Walton, Ryan B.
- Venue
- Computers & Industrial Engineering
- Publisher
- Elsevier BV
- Published
- 2024-07
- Volume
- 193
- Pages
- 110241
- ISSN
- 0360-8352 (ISSN-L)
- OpenAlex
- W4397289383
- Cited by
- 33
- References
- 52
- Citations by year
- 2026: 20 · 2025: 11 · 2024: 2
- FWCI
- 6.77
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Computers & Industrial Engineering (publishedVersion)
- SSRN Electronic Journal (acceptedVersion)
- Funders
- U.S. Air Force
- U.S. Department of Defense
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Social Sciences › Business, Management and Accounting › Management Information Systems › Big Data and Business Intelligence
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Applied Advanced Technologies
- Keywords
- digital twin, prescriptive analytics, real-time decision making, adaptive decision-making, digital twin architecture, Internet of Things, virtual reality, response time, system life cycle, synchronization
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