Digital Twin Technology for Sustainable Industrial Operations

Authors

  • Erlita Sulistiati Universitas Mahakarya Asia Author
  • Bustomi Bustomi Institut Pertanian Bogor Author
  • Guslila Sari Nasution Universitas Riau Indonesia Author
  • Atina Salamah Kementrian Agama Jawa Tengah Author
  • Rian Ardianto Universitas Harapan Bangsa Author

Keywords:

Digital Twin, Sustainable Operations, Industry 5.0, Industrial Sustainability, Cyber-Physical Systems.

Abstract

Digital Twin technology has emerged as a strategic enabler for sustainable industrial transformation by integrating physical operations, virtual representations, predictive analytics, and sustainability-oriented decision support into a unified cyber–physical environment. This study aims to develop and analytically evaluate a comprehensive Digital Twin framework capable of supporting sustainable industrial operations through the integration of operational efficiency, energy performance, resource optimization, and system resilience dimensions. A non-empirical system design approach was employed to construct a multilayer architecture consisting of physical operation, data acquisition, communication and synchronization, digital twin modeling, analytics and optimization, and sustainability decision-support layers. Technical evaluation was conducted through model-based simulation and analytical assessment using standardized sustainability and operational indicators. The findings demonstrate that the proposed framework strengthens operational visibility, predictive maintenance capability, energy efficiency, resource utilization, responsiveness, and resilience through continuous interaction between physical and virtual environments. The analysis further indicates that Digital Twin integration facilitates circularity, sustainability governance, and Industry 5.0 readiness by enabling adaptive and data-driven industrial decision making. The study contributes a holistic conceptual framework that advances the understanding of Digital Twin technology as a sustainability-enabling infrastructure for future industrial systems.

 

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References

Ba, L., Tangour, F., El Abbassi, I., & Absi, R. (2025). Analysis of digital twin applications in energy efficiency: A systematic review. Sustainability, 17(8), 3560. https://doi.org/10.3390/su17083560.

Badenko, V., Bolshakov, N., Celani, A., & Puglisi, V. (2024). Principles for sustainable integration of BIM and digital twin technologies in industrial infrastructure. Sustainability, 16(22), 9885. https://doi.org/10.3390/su16229885.

Barata, J., & Kayser, I. (2024). How will the digital twin shape the future of industry 5.0?. Technovation, 134, 103025. https://doi.org/10.1016/j.technovation.2024.103025.

Barni, A., Fontana, A., Menato, S., Sorlini, M., & Canetta, L. (2018, September). Exploiting the digital twin in the assessment and optimization of sustainability performances. In 2018 International conference on intelligent systems (IS) (pp. 706-713). IEEE.

Bhandal, R., Meriton, R., Kavanagh, R. E., & Brown, A. (2022). The application of digital twin technology in operations and supply chain management: a bibliometric review. Supply Chain Management: An International Journal, 27(2), 182-206. https://doi.org/10.1108/SCM-01-2021-0053.

Botín-Sanabria, D. M., Mihaita, A. S., Peimbert-García, R. E., Ramírez-Moreno, M. A., Ramírez-Mendoza, R. A., & Lozoya-Santos, J. D. J. (2022). Digital twin technology challenges and applications: A comprehensive review. Remote Sensing, 14(6), 1335. https://doi.org/10.3390/rs14061335.

De Felice, F., Singh, N., Ferraro, A., Garofalo, A., Acampora, L., & Petrillo, A. (2026). IoT and Digital Twin Integration for Sustainable Textile Manufacturing towards industry 5.0: GrEen Network. Procedia Computer Science, 277, 1508-1517. https://doi.org/10.1016/j.procs.2026.02.189.

Franciosi, C., Miranda, S., Veneroso, C. R., & Riemma, S. (2022). Improving industrial sustainability by the use of digital twin models in maintenance and production activities. IFAC-PapersOnLine, 55(19), 37-42. https://doi.org/10.1016/j.ifacol.2022.09.215.

He, B., & Bai, K. J. (2021). Digital twin-based sustainable intelligent manufacturing: a review. Advances in Manufacturing, 9(1), 1-21.

Jiao, Z., Du, X., Liu, Z., Liu, L., Sun, Z., & Shi, G. (2023). Sustainable operation and maintenance modeling and application of building infrastructures combined with digital twin framework. Sensors, 23(9), 4182. https://doi.org/10.3390/s23094182.

Kamble, S. S., Gunasekaran, A., Parekh, H., Mani, V., Belhadi, A., & Sharma, R. (2022). Digital twin for sustainable manufacturing supply chains: Current trends, future perspectives, and an implementation framework. Technological Forecasting and Social Change, 176, 121448. https://doi.org/10.1016/j.techfore.2021.121448.

Mane, S., Dhote, R. R., Sinha, A., & Thirumalaiswamy, R. (2024). Digital twin in the chemical industry: A review. Digital Twins and Applications, 1(2), 118-130. https://doi.org/10.1049/dgt2.12019.

Melesse, T. Y. (2025). Digital twin-based applications in crop monitoring. Heliyon, 11(2). https://doi.org/10.1016/j.heliyon.2025.e42137.

Mohanraj, R., & Balaji, S. N. (2026). Digital twin technology: A comprehensive review of modeling, applications, challenges and future directions in complex system integration. Archives of Computational Methods in Engineering, 33(3), 3291-3316.

Mousavi, Y., Gharineiat, Z., Karimi, A. A., McDougall, K., Rossi, A., & Gonizzi Barsanti, S. (2024). Digital twin technology in built environment: A review of applications, capabilities and challenges. Smart Cities, 7(5), 2594-2615. https://doi.org/10.3390/smartcities7050101.

Omrany, H., Mehdipour, A., & Oteng, D. (2024). Digital twin technology and social sustainability: Implications for the construction industry. Sustainability, 16(19), 8663. https://doi.org/10.3390/su16198663.

Park, K. T., Lee, D., & Noh, S. D. (2020). Operation procedures of a work-center-level digital twin for sustainable and smart manufacturing. International Journal of Precision Engineering and Manufacturing-Green Technology, 7(3), 791-814. https://doi.org/10.1007/s40684-020-00227-1.

Resman, M., Herakovič, N., & Debevec, M. (2025). Integrating digital twin technology to achieve higher operational efficiency and sustainability in manufacturing systems. Systems, 13(3), 180. https://doi.org/10.3390/systems13030180.

Sajadieh, S. M. M., & Noh, S. D. (2025). A review of digital twin integration in circular manufacturing for sustainable industry transition. Sustainability, 17(16), 7316. https://doi.org/10.3390/su17167316.

Schwark, F., Dawel, L., & Pehlken, A. (2023). Sustainability Digital Twin: a tool for the manufacturing industry. Procedia CIRP, 116, 143-148. https://doi.org/10.1016/j.procir.2023.02.025.

Singh, M., Srivastava, R., Fuenmayor, E., Kuts, V., Qiao, Y., Murray, N., & Devine, D. (2022). Applications of digital twin across industries: A review. Applied Sciences, 12(11), 5727. https://doi.org/10.3390/app12115727.

Warke, V., Kumar, S., Bongale, A., & Kotecha, K. (2021). Sustainable development of smart manufacturing driven by the digital twin framework: A statistical analysis. Sustainability, 13(18), 10139. https://doi.org/10.3390/su131810139.

Yu, W., Patros, P., Young, B., Klinac, E., & Walmsley, T. G. (2022). Energy digital twin technology for industrial energy management: Classification, challenges and future. Renewable and Sustainable Energy Reviews, 161, 112407. https://doi.org/10.1016/j.rser.2022.112407.

Zhang, Z., Wei, Z., Court, S., Yang, L., Wang, S., Thirunavukarasu, A., & Zhao, Y. (2024). A review of digital twin technologies for enhanced sustainability in the construction industry. Buildings, 14(4), 1113. https://doi.org/10.3390/buildings14041113.

Zhen, Z., & Yao, Y. (2025). The confluence of digital twin and blockchan technologies in Industry 5.0: Transforming supply chain management for innovation and sustainability. Journal of the Knowledge Economy, 16(1), 5295-5321. https://doi.org/10.1007/s13132-024-02151-0.

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Published

2026-06-08

How to Cite

Digital Twin Technology for Sustainable Industrial Operations. (2026). Technema: Journal of Intelligent Engineering and Computing, 1(2), 13-22. https://sovereignresearch.org/technema/article/view/153