Part data integration in the Shop Floor Digital Twin: Mobile and cloud technologies to enable a manufacturing execution system
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In the reviewed articles, DT was also used to evaluate the performances of a cloud-based DT, mainly aimed at verifying the speed with which data are updated in a cloud environment.
“- 8) Finally, the DT was also used to evaluate the 'Performances of a cloud-based DT' , that are mainly aimed at verifying the speed with which the data are updated in a cloud environment [74,75].”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [74]
The only reviewed articles that actually perform control of the real system are ad-hoc systems, meaning they used open protocols and programmable boards.
“The only articles that actually perform a control of the real system (i.e. in Table 1, column 'Control of the real system from the digital twin') are ' ad-hoc systems ' [43,74,75], meaning that they used open protocols and programmable boards.”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [74]
Cites
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 · see citing works
About 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 · cited 2× · see citing works
“…to implement Digital Twins is one of the benefits of data collection: large amounts of data enable the construction of simulations of different scenarios, which can be useful to make predictions about behaviors or failures, according to the latest data obtained from the physical twin [5,28].”
BackgroundMethodCyber-Physical Systems Security—A Survey
Humayed, A., Lin, J., Li, F., & Luo, B. (2017) · IEEE Internet of Things Journal · doi:10.1109/jiot.2017.2703172 · Cited by 1,185 · see citing works
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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 · see citing works
Review of digital twin applications in manufacturing
Cimino, C., Negri, E., & Fumagalli, L. (2019) · Computers in Industry · doi:10.1016/j.compind.2019.103130 · Cited by 874 · see citing works
Lim, K. Y. H., Zheng, P., & Chen, C.-H. (2020) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-019-01512-w · Cited by 700 · see citing works
Framework for a digital twin in manufacturing: Scope and requirements
Shao, G., & Helu, M. (2020) · Manufacturing Letters · doi:10.1016/j.mfglet.2020.04.004 · Cited by 292 · see citing works
Data construction method for the applications of workshop digital twin system
Kong, T., Hu, T., Zhou, T., & Ye, Y. (2021) · Journal of Manufacturing Systems · doi:10.1016/j.jmsy.2020.02.003 · Cited by 169 · see citing works
Probabilistic machine learning based predictive and interpretable digital twin for dynamical systems
Tripura, T., Desai, A. S., Adhikari, S., & Chakraborty, S. (2023) · Computers & Structures · doi:10.1016/j.compstruc.2023.107008 · Cited by 47 · see citing works
Cyber Physical Systems for Industry 4.0: Towards Real Time Virtual Reality in Smart Manufacturing
Frontoni, E., Loncarski, J., Pierdicca, R., Bernardini, M., & Sasso, M. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-95282-6_31 · Cited by 42 · see citing works
- Authors
- Urbina Coronado, P. D., Lynn, R., Louhichi, W., Parto, M., Wescoat, E., & Kurfess, T.
- Affiliations
- Georgia Institute of Technology (US)
- Venue
- Journal of Manufacturing Systems
- Publisher
- Elsevier BV
- Published
- 2018-07
- Volume
- 48
- Pages
- 25-33
- ISSN
- 0278-6125 (ISSN-L)
- OpenAlex
- W2792233253
- Cited by
- 267
- References
- 3
- Citations by year
- 2026: 7 · 2025: 32 · 2024: 36 · 2023: 41 · 2022: 38 · 2021: 45 · 2020: 41 · 2019: 23 · 2018: 4
- FWCI
- 23.41
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Manufacturing Systems (publishedVersion)
- Funders
- CONACYT
- NSF (IIP-1631803, CMMI-1646013, DGE-1650044)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Flexible and Reconfigurable Manufacturing Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Industrial Automation and Control Systems
- Keywords
- manufacturing execution system, MTConnect, machine tool data, Android devices, cloud computing, data integration, small manufacturing enterprises, titanium parts, production monitoring, production control
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