Operational Digital Twins: Definition and Common Use Cases
Publication: Computing in Civil Engineering 2023
ABSTRACT
Digital twins (DT) have recently gained significant interest among architecture, engineering, construction, and operations (AECO) industry professionals and researchers. However, there is no consensus on the definition of digital twins to the point that some practitioners use building information models (BIM) and digital twins synonymously. This research focuses on developing a scope definition for the identification and classification of DT use cases. The results will help researchers and industry practitioners with planning the implementation of operational digital twins. A detailed review of the literature was conducted to find the existing definitions of operational digital twins. Afterward, an extensive review of use cases of operational digital twins was completed. Furthermore, these use cases were defined through a categorical content analysis, and they were placed within an existing widely used ontology. Examples of operational DT use cases include remote asset monitoring, remote asset control, and asset performance prediction. Use cases identified in this paper were reviewed by leading experts in the DT community. The findings of this paper will benefit researchers and industry practitioners in planning for digital twin implementations by providing a common language with attributes to define specific DT use cases.
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REFERENCES
Agostinelli, S., F. Cumo, G. Guidi, and C. Tomazzoli. (2021). “Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence.” Energies, 14 (8): 2338. https://doi.org/10.3390/en14082338.
Aivaliotis, P., K. Georgoulias, and G. Chryssolouris. (2019). “The use of Digital Twin for predictive maintenance in manufacturing.” International Journal of Computer Integrated Manufacturing, 32 (11): 1067–1080. https://doi.org/10.1080/0951192X.2019.1686173.
Akanmu, A., C. Anumba, and J. Messner. (2014). “Active monitoring and control of light fixtures during building construction and operation: Cyber-physical systems approach.” Journal of Architectural Engineering, ASCE, 20 (2). https://doi.org/10.1061/(ASCE)AE.1943-5568.0000140.
Al-Sehrawy, R., and B. Kumar. (2021). “Digital Twins in Architecture, Engineering, Construction and Operations. A Brief Review and Analysis.” Proceedings of the 18th International Conference on Computing in Civil and Building Engineering, Lecture Notes in Civil Engineering, E. Toledo Santos and S. Scheer, eds., 924–939. Cham: Springer International Publishing.
Arsiwala, A., F. Elghaish, and M. Zoher. (2023). “Digital twin with Machine learning for predictive monitoring of CO2 equivalent from existing buildings.” Energy and Buildings, 284: 112851. https://doi.org/10.1016/j.enbuild.2023.112851.
Bonci, A., A. Carbonari, A. Cucchiarelli, L. Messi, M. Pirani, and M. Vaccarini. (2019). “A cyber-physical system approach for building efficiency monitoring.” Automation in Construction, 102: 68–85. https://doi.org/10.1016/j.autcon.2019.02.010.
Brilakis, I., Y. Pan, A. Borrmann, H.-G. Mayer, F. Rhein, C. Vos, E. Pettinato, and S. Wagner. (2019). Built Environment Digital Twining. Report. International Workshop on Built Environment Digital Twinning presented by TUM Institute for Advanced Study and Siemens AG.
Digital Twin Consortium. (2020). “Definition of a Digital Twin.” https://www.digitaltwinconsortium.org/initiatives/the-definition-of-a-digital-twin/.
Edwards, C., D. L. Morales, C. Haas, S. Narasimhan, and G. Cascante. (2023). “Digital twin development through auto-linking to manage legacy assets in nuclear power plants.” Automation in Construction, 148: 104774. https://doi.org/10.1016/j.autcon.2023.104774.
Gelernter, D. (1993). Mirror Worlds: or the Day Software Puts the Universe in a Shoebox……How It Will Happen and What It Will Mean. Oxford University Press.
Grieves, M. (2002). Completing the Cycle: Using PLM Information in the Sales and Service Functions [Slides]. SME Management Forum, Troy, MI. 2002.
Hosamo, H. H., P. R. Svennevig, K. Svidt, D. Han, and H. K. Nielsen. (2022). “A Digital Twin predictive maintenance framework of air handling units based on automatic fault detection and diagnostics.” Energy and Buildings, 261: 111988. https://doi.org/10.1016/j.enbuild.2022.111988.
Jiang, F., L. Ma, T. Broyd, and K. Chen. (2021). “Digital twin and its implementations in the civil engineering sector.” Automation in Construction, 130: 103838. https://doi.org/10.1016/j.autcon.2021.103838.
Kong, L. C. W., S. Harper, D. Mitchell, J. Blanche, T. Lim, and D. Flynn. (2020). “Interactive Digital Twins Framework for Asset Management Through Internet.” 2020 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT), 1–7.
Kreider, R. G., and J. I. Messner. (2013). “The Uses of BIM: Classifying and Selecting BIM Uses”. Version 0.9, September, The Pennsylvania State University, University Park, PA, USA. http://bim.psu.edu.
Liu, M., S. Fang, H. Dong, and C. Xu. (2021). “Review of digital twin about concepts, technologies, and industrial applications.” Journal of Manufacturing Systems, Digital Twin towards Smart Manufacturing and Industry 4.0, 58: 346–361. https://doi.org/10.1016/j.jmsy.2020.06.017.
Lu, Q., X. Xie, A. K. Parlikad, and J. M. Schooling. (2020). “Digital twin-enabled anomaly detection for built asset monitoring in operation and maintenance.” Automation in Construction, 118: 103277. https://doi.org/10.1016/j.autcon.2020.103277.
Mauro, F., and A. A. Kana. (2023). “Digital twin for ship life-cycle: A critical systematic review.” Ocean Engineering, 269: 113479. https://doi.org/10.1016/j.oceaneng.2022.113479.
NIBS. (2023). BIM Use Definitions, Draft, US National BIM Standard, Version 4, Washington, D.C.
Onaji, I., D. Tiwari, P. Soulatiantork, B. Song, and A. Tiwari. (2022). “Digital twin in manufacturing: conceptual framework and case studies.” International Journal of Computer Integrated Manufacturing, 35 (8): 831–858. https://doi.org/10.1080/0951192X.2022.2027014.
Seaton, H., C. Savian, S. Sepasgozar, and A. Sawhney. (2022). Digital twins from design to handover of constructed assets. Royal Institution of Chartered Surveyors (RICS).
Shim, C.-S., N.-S. Dang, S. Lon, and C.-H. Jeon. (2019). “Development of a bridge maintenance system for prestressed concrete bridges using 3D digital twin model.” Structure and Infrastructure Engineering, 15 (10): 1319–1332. https://doi.org/10.1080/15732479.2019.1620789.
Singh, M., R. Srivastava, E. Fuenmayor, V. Kuts, Y. Qiao, N. Murray, and D. Devine. (2022). “Applications of Digital Twin across Industries: A Review.” Applied Sciences, 12 (11): 5727. https://doi.org/10.3390/app12115727.
Wang, W., T. Hong, N. Li, R. Q. Wang, and J. Chen. (2019). “Linking energy-cyber-physical systems with occupancy prediction and interpretation through WiFi probe-based ensemble classification.” Applied Energy, 236: 55–69. https://doi.org/10.1016/j.apenergy.2018.11.079.
Xie, X., J. Merino, N. Moretti, P. Pauwels, J. Y. Chang, and A. Parlikad. (2023). “Digital twin enabled fault detection and diagnosis process for building HVAC systems.” Automation in Construction, 146: 104695. https://doi.org/10.1016/j.autcon.2022.104695.
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Published In
Computing in Civil Engineering 2023
Pages: 121 - 128
History
Published online: Jan 25, 2024
ASCE Technical Topics:
- Architectural engineering
- Asset management
- Building information modeling
- Building management
- Buildings
- Business management
- Case studies
- Construction engineering
- Engineering fundamentals
- Financial management
- High-rise buildings
- Industries
- Information management
- Methodology (by type)
- Organizations
- Practice and Profession
- Research methods (by type)
- Structural engineering
- Structures (by type)
- Terminology and definition
Authors
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