Machine Learning based Digital Twin Framework for Production Optimization in Petrochemical Industry
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Smart manufacturing technologies, such as optimization of key manufacturing features and production framework improvements, benefit significantly from Digital Twin integration.
“Additionally, smart manufacturing technologies, such as the optimization of key manufacturing features and production framework improvements, benefit significantly from Digital Twin integration [108,109].”
From Analysis of Digital Twin Applications in Energy Efficiency: A Systematic Review (2025) · cites this paper as [109]
Cites
Digital twin-driven product design, manufacturing and service with big data
Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., & Sui, F. (2018) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-017-0233-1 · Cited by 2,920 · see citing works
Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.01.021 · Cited by 2,628 · see citing works
Reengineering aircraft structural life prediction using a digital twin
Tuegel, E. J., Ingraffea, A. R., Eason, T. G., & Spottswood, S. M. (2011) · International Journal of Aerospace Engineering · doi:10.1155/2011/154798 · Cited by 1,119 · see citing works
Digital twin-driven rapid individualised designing of automated flow-shop manufacturing system
Liu, Q., Zhang, H., Leng, J., & Chen, X. (2019) · International Journal of Production Research · doi:10.1080/00207543.2018.1471243 · Cited by 370 · see citing works
Big data reduction framework for value creation in sustainable enterprises
Rehman, M. H. U., Chang, V., Batool, A., & Wah, T. Y. (2016) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2016.05.013 · Cited by 279 · see citing works
The Airframe Digital Twin: Some Challenges to Realization
Tuegel, E. (2012) · 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference<BR>20th AIAA/ASME/AHS Adaptive Structures Conference<BR>14th AIAA · doi:10.2514/6.2012-1812 · Cited by 255 · see citing works
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Digital twin: Enabling technologies, challenges and open research
Fuller, A., Fan, Z., Day, C., & Barlow, C. (2020) · IEEE Access · doi:10.1109/access.2020.2998358 · Cited by 2,965 · see citing works
Belhadi, A., Mani, V., Kamble, S. S., Khan, S. A. R., & Verma, S. (2024) · Annals of Operations Research · doi:10.1007/s10479-021-03956-x · Cited by 797 · see citing works
Rathore, M. M., Shah, S. A., Shukla, D., Bentafat, E., & Bakiras, S. (2021) · IEEE Access · doi:10.1109/access.2021.3060863 · Cited by 616 · see citing works
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 · see citing works
A survey on AI-driven digital twins in Industry 4.0: smart manufacturing and advanced robotics
Huang, Z., Shen, Y., Li, J., Fey, M., & Brecher, C. (2021) · Sensors · doi:10.3390/s21196340 · Cited by 418 · see citing works
IoT and digital twin enabled smart tracking for safety management
Zhao, Z., Shen, L., Yang, C., Wu, W., Zhang, M., & Huang, G. Q. (2021) · Computers & Operations Research · doi:10.1016/j.cor.2020.105183 · Cited by 155 · see citing works
Zeb, S., Mahmood, A., Hassan, S. A., Piran, M. J., Gidlund, M., & Guizani, M. (2022) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2021.103309 · Cited by 132 · see citing works
Warke, V., Kumar, S., Bongale, A., & Kotecha, K. (2021) · Sustainability · doi:10.3390/su131810139 · Cited by 103 · see citing works
Digital twin for integration of design-manufacturing-maintenance: an overview
Fu, Y., Zhu, G., Zhu, M., & Xuan, F. (2022) · Chinese Journal of Mechanical Engineering · doi:10.1186/s10033-022-00760-x · Cited by 98 · see citing works
Analysis of Digital Twin Applications in Energy Efficiency: A Systematic Review
Ba, L., Tangour, F., El Abbassi, I., & Absi, R. (2025) · Sustainability · doi:10.3390/su17083560 · Cited by 96 · see citing works
- Authors
- Min, Q., Lu, Y., Liu, Z., Su, C., & Wang, B.
- Affiliations
- Dalian University of Technology (CN)
- Lenovo (China) (CN)
- Corresponding author
- Liu, Zhiyong
- Venue
- International Journal of Information Management
- Publisher
- Elsevier BV
- Published
- 2019-12
- Volume
- 49
- Pages
- 502-519
- ISSN
- 0268-4012 (ISSN-L)
- OpenAlex
- W2947324800
- Cited by
- 436
- References
- 6
- Citations by year
- 2026: 11 · 2025: 62 · 2024: 95 · 2023: 90 · 2022: 81 · 2021: 72 · 2020: 20 · 2019: 5
- FWCI
- 32.84
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Information Management (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Natural Science Foundation of China (71421001, 71431002, 71772002, 71872033)
- Jilin Office of Philosophy and Social Science
- Natural Science Foundation of Liaoning Province (20180550433)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Applied Advanced Technologies
- Keywords
- digital twin, petrochemical industry, production optimization, production control, Industrial Internet of Things, smart manufacturing, high-dimensional data, process manufacturing
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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.
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