The Digital Twin Technology: A Scoping Review of Characterization and Implementation Through Business IT Perspectives
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Abstract
Digital twin is a revolutionizing technology. It involves sophisticated models such as real-time data, history data, simulation, machine learning, sensor updates which can reflect almost every detail of the physical objects, procedures, and services. Digital twin technology would be replicated the physical world into a virtual world in the future. Digital twin technology is considered state-of-the-art, but full implementation has yet to occur due to technical challenges and delays. The researchers have to create all the unique and specialized components of the thing or system and collect and combine a massive amount of diverse data. Since, many researchers and employees from some industries such as architecture, health care and engineering are still not completely understood about the technologies and tools used in digital twin technology. This paper illustrates scoping reviews of the characterization, implementation processes of digital twin in business information technology within 5 years period from 2018 to 2022. Furthermore, Digital Twin current applications in three different territories are also outlined in this paper. The purpose of the paper is to understand systematically about the digital twin technology process in different fields.
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Copyright (c) 2023 Hein Ko Ko Htet, Dr. Indrianawati Usman, Dr. M. Yusak Anshori
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References
A Scoping Review of Digital Twins in the Context of the Covid-19 Pandemic _ Enhanced Reader. (n.d.).
Ashtari Talkhestani, B., Jung, T., Lindemann, B., Sahlab, N., Jazdi, N., Schloegl, W., & Weyrich, M. (2019). An architecture of an Intelligent Digital Twin in a Cyber-Physical Production System. At-Automatisierungstechnik, 67(9), 762–782. https://doi.org/10.1515/auto-2019-0039
Barricelli, B. R., Casiraghi, E., Gliozzo, J., Petrini, A., & Valtolina, S. (2020). Human Digital Twin for Fitness Management. IEEE Access, 8, 26637–26664. https://doi.org/10.1109/ACCESS.2020.2971576
Baruffaldi, G., Accorsi, R., & Manzini, R. (2019). Warehouse management system customization and information availability in 3pl companies: A decision-support tool. Industrial Management and Data Systems, 119(2), 251–273. https://doi.org/10.1108/IMDS-01-2018-0033
Botín-Sanabria, D. M., Mihaita, S., Peimbert-García, R. E., Ramírez-Moreno, M. A., Ramírez-Mendoza, R. A., & Lozoya-Santos, J. de J. (2022). Digital Twin Technology Challenges and Applications: A Comprehensive Review. In Remote Sensing (Vol. 14, Issue 6). MDPI. https://doi.org/10.3390/rs14061335
Bottani, E., & Murino, T. (2017). From the Cyber-Physical System to the Digital Twin: the process development for behaviour modelling of a Cyber Guided Vehicle in M2M logic SERAMIS-Sensor-Enabled Real-world Awareness for Management Information Systems View project Wearable augmented reality for employee safety in manufacturing systems (W-Artemys) View project. https://www.researchgate.net/publication/334113041
Canedo, A. (2016, November 21). Industrial IoT lifecycle via digital twins. 2016 International Conference on Hardware/Software Codesign and System Synthesis, CODES+ISSS 2016. https://doi.org/10.1145/2968456.2974007
Delen, D., & Demirkan, H. (2013). Data, information and analytics as services. Decision Support Systems, 55(1), 359–363. https://doi.org/10.1016/J.DSS.2012.05.044
Fuller, A., Fan, Z., Day, C., & Barlow, C. (2020). Digital Twin: Enabling Technologies, Challenges and Open Research. IEEE Access, 8, 108952–108971. https://doi.org/10.1109/ACCESS.2020.2998358
Guerra, R. H., Quiza, R., Villalonga, A., Arenas, J., & Castano, F. (2019). Digital Twin-Based Optimization for Ultraprecision Motion Systems with Backlash and Friction. IEEE Access, 7, 93462–93472. https://doi.org/10.1109/ACCESS.2019.2928141
Jeong, D. Y., Baek, M. S., Lim, T. B., Kim, Y. W., Kim, S. H., Lee, Y. T., Jung, W. S., & Lee, I. B. (2022a). Digital Twin: Technology Evolution Stages and Implementation Layers with Technology Elements. IEEE Access, 10, 52609–52620. https://doi.org/10.1109/ACCESS.2022.3174220
Jeong, D. Y., Baek, M. S., Lim, T. B., Kim, Y. W., Kim, S. H., Lee, Y. T., Jung, W. S., & Lee, I. B. (2022b). Digital Twin: Technology Evolution Stages and Implementation Layers with Technology Elements. IEEE Access, 10, 52609–52620. https://doi.org/10.1109/ACCESS.2022.3174220
Karve, P. M., Guo, Y., Kapusuzoglu, B., Mahadevan, S., & Haile, M. A. (2020). Digital twin approach for damage-tolerant mission planning under uncertainty. Engineering Fracture Mechanics, 225, 106766. https://doi.org/10.1016/J.ENGFRACMECH.2019.106766
Laaki, H., Miche, Y., & Tammi, K. (2019). Prototyping a Digital Twin for Real Time Remote Control over Mobile Networks: Application of Remote Surgery. IEEE Access, 7, 20235–20336. https://doi.org/10.1109/ACCESS.2019.2897018
Laamarti, F., Badawi, H. F., Ding, Y., Arafsha, F., Hafidh, B., & Saddik, A. el. (2020). An ISO/IEEE 11073 Standardized Digital Twin Framework for Health and Well-Being in Smart Cities. IEEE Access, 8, 105950–105961. https://doi.org/10.1109/ACCESS.2020.2999871
Liu, M., Fang, S., Dong, H., & Xu, C. (2021). Review of digital twin about concepts, technologies, and industrial applications. Journal of Manufacturing Systems, 58, 346–361. https://doi.org/10.1016/j.jmsy.2020.06.017
Macchi, M., Roda, I., Negri, E., & Fumagalli, L. (2018). Exploring the role of Digital Twin for Asset Lifecycle Management. IFAC-PapersOnLine, 51(11), 790–795. https://doi.org/10.1016/J.IFACOL.2018.08.415
Madni, A. M., Madni, C. C., & Lucero, S. D. (n.d.). Leveraging Digital Twin Technology in Model-Based Systems Engineering. https://doi.org/10.3390/systems7010007
Mohammadi, ), Jahromi, A., Khademi, M. G., Alighanbari, H., Khabiri, M., & Jahromi, M. M. (2018). Terms and conditions Privacy policy Understanding kid’s digital twin Publication Stage: Final Source: Scopus.
Olatunji, O. O., Adedeji, P. A., Madushele, N., & Jen, T. C. (2021). Overview of Digital Twin Technology in Wind Turbine Fault Diagnosis and Condition Monitoring. Proceedings of 2021 IEEE 12th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2021, 201–207. https://doi.org/10.1109/ICMIMT52186.2021.9476186
Opoku, D. G. J., Perera, S., Osei-Kyei, R., & Rashidi, M. (2021). Digital twin application in the construction industry: A literature review. In Journal of Building Engineering (Vol. 40). Elsevier Ltd. https://doi.org/10.1016/j.jobe.2021.102726
Power Digital Solutions, G. (2016). GE Power Digital Solutions GE Digital Twin.
Qi, Q., Tao, F., Hu, T., Anwer, N., Liu, A., Wei, Y., Wang, L., & Nee, A. Y. C. (2021a). Enabling technologies and tools for digital twin. Journal of Manufacturing Systems, 58, 3–21. https://doi.org/10.1016/j.jmsy.2019.10.001
Qi, Q., Tao, F., Hu, T., Anwer, N., Liu, A., Wei, Y., Wang, L., & Nee, A. Y. C. (2021b). Enabling technologies and tools for digital twin. Journal of Manufacturing Systems, 58, 3–21. https://doi.org/10.1016/j.jmsy.2019.10.001
Rassõlkin, A., Orosz, T., Demidova, G. L., Kuts, V., Rjabtšikov, V., Vaimann, T., & Kallaste, A. (2021). Implementation of digital twins for electrical energy conversion systems in selected case studies. Proceedings of the Estonian Academy of Sciences, 70(1), 19–39. https://doi.org/10.3176/proc.2021.1.03
Roy, R. B., Mishra, D., Pal, S. K., Chakravarty, T., Panda, S., Chandra, M. G., Pal, A., Misra, P., Chakravarty, D., & Misra, S. (2020). Digital twin: current scenario and a case study on a manufacturing process. International Journal of Advanced Manufacturing Technology, 107(9–10), 3691–3714. https://doi.org/10.1007/s00170-020-05306-w
Shengli, W. (2021). Is Human Digital Twin possible? Computer Methods and Programs in Biomedicine Update, 1, 100014. https://doi.org/10.1016/j.cmpbup.2021.100014
Singh, S., Weeber, M., & Birke, K. P. (2021). Advancing digital twin implementation: A toolbox for modelling and simulation. Procedia CIRP, 99, 567–572. https://doi.org/10.1016/j.procir.2021.03.078
Tao, F., Zhang, H., Liu, A., & Nee, A. Y. C. (2019). Digital Twin in Industry: State-of-the-Art. IEEE Transactions on Industrial Informatics, 15(4), 2405–2415. https://doi.org/10.1109/TII.2018.2873186
VanDerHorn, E., & Mahadevan, S. (2021). Digital Twin: Generalization, characterization and implementation. Decision Support Systems, 145. https://doi.org/10.1016/j.dss.2021.113524
Verdouw, C. N., & Kruize, J. W. (n.d.). Digital twins in farm management: illustrations from the FIWARE accelerators SmartAgriFood and Fractals.
White, G., Zink, A., Codecá, L., & Clarke, S. (n.d.). A Digital Twin Smart City for Citizen Feedback. https://www.scss.tcd.ie/
Wright, L., & Davidson, S. (2020). How to tell the difference between a model and a digital twin. Advanced Modeling and Simulation in Engineering Sciences, 7(1). https://doi.org/10.1186/s40323-020-00147-4
Zheng, Y., Yang, S., & Cheng, H. (2019). An application framework of digital twin and its case study. Journal of Ambient Intelligence and Humanized Computing, 10(3), 1141–1153. https://doi.org/10.1007/s12652-018-0911-3
Zhou, C., Xu, J., Miller-Hooks, E., Zhou, W., Chen, C. H., Lee, L. H., Chew, E. P., & Li, H. (2021a). Analytics with digital-twinning: A decision support system for maintaining a resilient port. Decision Support Systems, 143, 113496. https://doi.org/10.1016/J.DSS.2021.113496
Zhou, C., Xu, J., Miller-Hooks, E., Zhou, W., Chen, C. H., Lee, L. H., Chew, E. P., & Li, H. (2021b). Analytics with digital-twinning: A decision support system for maintaining a resilient port. Decision Support Systems, 143, 113496. https://doi.org/10.1016/J.DSS.2021.113496