DIGITAL TWIN IN CONSTRUCTION INDUSTRY: A REVIEW ON DEFINITION, APPLICATION AND CHALLENGES OF ADOPTION
DOI:
https://doi.org/10.11113/aej.v16.24473Keywords:
Digital Twin, Construction Industry, Definition, Application, ChallengesAbstract
The construction industry is pivotal in driving Malaysia’s Gross Domestic Product (GDP), contributing to economic growth and infrastructure developments. However, with the complexity and large-scale infrastructure projects, there is a growing demand for technological advancements in construction, maintenance and monitoring. Digital Twin (DT) technology, known for its real-time data, predictive analysis, and simulation capabilities, presents a promising solution. A systematic literature review (SLR) was employed, and a total of 1087 publications were retrieved from the Scopus database. After applying inclusion and exclusion criteria, only 140 studies were included for review in this paper. This paper aims to explore the definition, current state of DT applications in the lifecycle phases while highlighting the challenges posed in adopting DT. Digital Twin (DT) is a virtual representation of physical entities, processes, and real-time data that enables better monitoring, simulation, and predictive analysis throughout a project's lifecycle. The application of DT are virtual prototyping and simulation in planning and design stages, real-time progress tracking in construction stage, predictive and proactive maintenance during operation and maintenance and simulation of structural vulnerabilities and collapses sequence in demolition and recovery phases. The study also identifies challenges from four (4) main aspects: process, people, technology and policy. Key challenges include integrating data from multiple sources, resistance to new technologies, high software and hardware cost and concerns regarding confidentiality due to unclear data governance regulations. The findings offer valuable insights for industry practitioners, policymakers, and researchers aiming to leverage Digital Twin technology for a more sustainable and efficient construction industry.
References
Angjeliu, G., Coronelli, D., and Cardani, G. 2020. Development of the simulation model for Digital Twin applications in historical masonry buildings: The integration between numerical and experimental reality. Computers & Structures, 238: 106282. DOI: https://doi.org/10.1016/j.compstruc.2020.106282
Arowoiya, V. A., Moehler, R., and Fang, Y. 2023. Digital Twin Technology for Thermal Comfort and Energy Efficiency in Buildings: A State-of-the-Art and future directions. Energy and Built Environment. 5(5): 641-656. DOI: https://doi.org/10.1016/j.enbenv.2023.05.004
Biesinger, F., Meike, D., Kraß, B., and Weyrich, M. 2019. A digital twin for production planning based on cyber-physical systems: A Case Study for a Cyber-Physical System-Based Creation of a Digital Twin. Procedia CIRP. 79: 355-360. DOI: https://doi.org/10.1016/j.procir.2019.02.087
Boje, C., Guerriero, A., Kubicki, S., and Rezgui, Y. 2020. Towards a Semantic Construction Digital Twin: Directions for Future Research. Automation in Construction. 114: 103179. DOI: https://doi.org/10.1016/j.autcon.2020.103179
Botín Sanabria, D. M., Mihaita, A.-S., Peimbert-García, R. E., Ramírez-Moreno, M. A., Ramírez-Mendoza, R. A., and Lozoya-Santos, J. de J. 2022. Digital Twin Technology Challenges and Applications: A Comprehensive Review. Remote Sensing. 14(6): 1335. DOI: https://doi.org/10.3390/rs14061335
Briner, R. B., and Denyer, D. Systematic Review and Evidence Synthesis as a Practice and Scholarship Tool. 2012. United States: Oxford University Press. 112-129. Retrieved date: 2025, February 7. DOI: https://doi.org/10.1093/oxfordhb/9780199763986.013.0007
CIDB. 2023, November 20. Economic Impact of Madani Framework and Budget 2024 on the Construction Industry. Malaysia: Construction Industry Development Board (CIDB). https://www.cidb.gov.my/eng/economic impact of madani framework-and-budget-2024-on-the-construction-industry/ Retrieved date: 2025, February 7
Delgado, J. M., and Oyedele, L. 2021. Digital Twins for the built environment: learning from conceptual and process models in manufacturing. Advanced Engineering Informatics. 49: 101332. DOI: https://doi.org/10.1016/j.aei.2021.101332
Eastman, C. M., P. Teicholz, Sacks, R., and Liston, K. BIM Handbook: A Guide to Building Information Modeling For Owners. 2011. United States: John Wiley & Sons, Inc. 10(2): 93-282. Retrieved date: 2023, December 24. https://www.benardmakaa.com/wp-content/uploads/2021/11/BIM-Handbook_-A-Guide-to-Building-Information-Modeling-for-Owners-Designers-Engineers-Contractors-and-Facility-Managers-Wiley-2018.pdf
Ellul, C., Hamilton, N., Pieri, A., and Floros, G. (2024). Exploring Data for Construction Digital Twins: Building Health and Safety and Progress Monitoring Twins Using the Unreal Gaming Engine. Buildings. 14(7): 2216-2216. DOI: https://doi.org/10.3390/buildings14072216
Falagas, M. E., Pitsouni, E. I., Malietzis, G. A., and Pappas, G. 2008. Comparison of PubMed, Scopus, Web of Science, and Google Scholar: Strengths and Weaknesses. The FASEB Journal. 22(2): 338-342. DOI: https://doi.org/10.1096/fj.07-9492lsf
Frangopol, D. M., and Bocchini, P. 2011. Resilience As Optimization Criterion for the Rehabilitation of Bridges Belonging to a Transportation Network Subject to Earthquake. Structures Congress 2011. 1802-1811. DOI: https://doi.org/10.1061/41171(401)178
Fuller, A., Fan, Z., Day, C., and Barlow, C. 2020. Digital Twin: Enabling Technologies, Challenges and Open Research. IEEE Access. 8: 108952-108971. DOI: https://doi.org/10.1109/access.2020.2998358
Grant, M. J., and Booth, A. 2009. A Typology of reviews: an Analysis of 14 Review Types and Associated Methodologies. Health Information & Libraries Journal. 26(2): 91-108. DOI: https://doi.org/10.1111/j.1471-1842.2009.00848.x
Grieves, M., and Vickers, J. 2016. Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems. Transdisciplinary Perspectives on Complex Systems. 85-113. DOI: https://doi.org/10.1007/978-3-319-38756-7_4
Hielscher, T., Khalil, S., Virgona, N., and S.A. Hadigheh. 2023. A neural network based digital twin model for the structural health monitoring of reinforced concrete bridges. Structures. 57: 105248-105248. DOI: https://doi.org/10.1016/j.istruc.2023.105248
J. Vatn. Industry 4.0 and real-time synchronization of operation and maintenance. 2018. Norway: Taylor & Francis. 681-686. DOI: https://doi.org/10.1201/9781351174664-84 Retrieved date: 2025, February 7
Jiang, F., Ma, L., Broyd, T., and Chen, K. 2021. Digital twin and its implementations in the civil engineering sector. Automation in Construction. 130: 103838. DOI: https://doi.org/10.1016/j.autcon.2021.103838
Kaewunruen, S. Rail Infrastructure Resilience. 2022. San Diego: Woodhead Publishing. DOI: https://doi.org/10.1016/c2019-0-01267-8 Retrieved date: 2024, April 20
Kaewunruen, S., Sresakoolchai, J., and Lin, Y. 2021. Digital twins for managing railway maintenance and resilience. Open Research Europe. 1: 91. DOI: https://doi.org/10.12688/openreseurope.13806.2
Lin, Y.-C., and Cheung, W.-F. 2020. Developing WSN/BIM-Based Environmental Monitoring Management System for Parking Garages in Smart Cities. Journal of Management in Engineering. 36(3): 04020012. DOI: https://doi.org/10.1061/(asce)me.1943-5479.0000760
Love, P. E. D., and Matthews, J. 2019. The "how" of benefits management for digital technology: From engineering to asset management. Automation in Construction. 107(1): 102930. DOI: https://doi.org/10.1016/j.autcon.2019.102930
Lu, Y., Liu, Z., and Min, Q. 2021. A digital twin-enabled value stream mapping approach for production process reengineering in SMEs. International Journal of Computer Integrated Manufacturing. 34(7-8): 764-782. DOI: https://doi.org/10.1080/0951192x.2021.1872099
Mabkhot, M., Al-Ahmari, A., Salah, B., and Alkhalefah, H. 2018. Requirements of the Smart Factory System: A Survey and Perspective. Machines. 6(2): 23. DOI: https://doi.org/10.3390/machines6020023
Macchi, M., Roda, I., Negri, E., and Fumagalli, L. 2018. Exploring the role of Digital Twin for Asset Lifecycle Management. IFAC-PapersOnLine. 51(11): 790-795. DOI: https://doi.org/10.1016/j.ifacol.2018.08.415
Madubuike, O. C., and Anumba, C. J. 2023. Digital Twin-Based Health Care Facilities Management. Journal of Computing in Civil Engineering. 37(2): 1-11. DOI: https://doi.org/10.1061/jccee5.cpeng-4842
Moher, D., Liberati, A., Tetzlaff, J., and Altman, D. G. 2009. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA Statement. PLoS Medicine. 6(7): e1000097. DOI: https://doi.org/10.1371/journal.pmed.1000097
Negri, E., Fumagalli, L., and Macchi, M. 2017. A Review of the Roles of Digital Twin in CPS-based Production Systems. Procedia Manufacturing. 11: 939-948. DOI: https://doi.org/10.1016/j.promfg.2017.07.198
Opoku, A., and Ahmed, V. 2014. Embracing sustainability practices in UK construction organizations. Built Environment Project and Asset Management. 4(1): 90-107. DOI: https://doi.org/10.1108/bepam-02-2013-0001
Opoku, D.-G. J., Perera, S., Osei-Kyei, R., and Rashidi, M. 2021. Digital twin application in the construction industry: A literature review. Journal of Building Engineering. 40(1): 102726. DOI: https://doi.org/10.1016/j.jobe.2021.102726
Opoku, D.-G. J., Perera, S., Osei-Kyei, R., Rashidi, M., Famakinwa, T., and Bamdad, K. 2022. Drivers for Digital Twin Adoption in the Construction Industry: A Systematic Literature Review. Buildings. 12(2): 113. DOI: https://doi.org/10.3390/buildings12020113
Osei-Kyei, R., and Chan, A. P. C. 2015. Review of studies on the Critical Success Factors for Public-Private Partnership (PPP) projects from 1990 to 2013. International Journal of Project Management. 33(6): 1335-1346. DOI: https://doi.org/10.1016/j.ijproman.2015.02.008
R. Sivarethinamohan, and Reddy, R. S. 2024. Digital Twin for Smart City Resilience and Solutions. 605-619. DOI: https://doi.org/10.1002/9781394303564.ch25
Rafsanjani, H. N., and Nabizadeh, A. H. 2023. Towards Digital Architecture, Engineering, and Construction (AEC) Industry through Virtual Design and Construction (VDC) and Digital Twin. Energy and Built Environment. 4(2): 169-178. DOI: https://doi.org/10.1016/j.enbenv.2021.10.004
Sacks, R., Brilakis, I., Pikas, E., Xie, H. S., and Girolami, M. 2020. Construction with digital twin information systems. Data-Centric Engineering. 1(1): e14. DOI: https://doi.org/10.1017/dce.2020.16
Schrotter, G., and Hürzeler, C. 2020. The Digital Twin of the City of Zurich for Urban Planning. PFG - Journal of Photogrammetry, Remote Sensing and Geoinformation Science. 88(1): 99-112. DOI: https://doi.org/10.1007/s41064-020-00092-2
Shafto, M., Conroy, M., Doyle, R., Glassgen, E., Kemp, C., and LeMoigne, J. NASA Technology Roadmap: Modeling, Simulation, Information Technology and Processing Roadmap. 2010. Washington, D.C.: National Aeronautics and Space Administration (NASA). 11: 1-32
https://www.lpi.usra.edu/sbag/goals/capability_inputs/2015_Tech_11_modeling_simulation.pdf Retrieved date: 2023, August 11
Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., and Sui, F. 2018. Digital twin-driven product design, manufacturing and service with big data. The International Journal of Advanced Manufacturing Technology. 94(9-12): 3563-3576. DOI: https://doi.org/10.1007/s00170-017-0233-1
Tao, F., Zhang, C., Qi, Q., and Zhang, H. 2022. Digital twin maturity model. Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems (CIMS). 28(5): 1267-1281. DOI: https://doi.org/10.13196/j.cims.2022.05.001
Tao, F., Zhang, H., Liu, A., and Nee, A. Y. C. 2019. Digital Twin in Industry: State-of-the-Art. IEEE Transactions on Industrial Informatics. 15(4): 2405-2415. DOI: https://doi.org/10.1109/tii.2018.2873186
Tchana, Y., Ducellier, G., and Remy, S. 2019. Designing a unique Digital Twin for linear infrastructures lifecycle management. Procedia CIRP. 84: 545-549. DOI: https://doi.org/10.1016/j.procir.2019.04.176
Tuegel, E. 2012. The Airframe Digital Twin: Some Challenges to Realization. Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference. 1(53): 1-11. DOI: https://doi.org/10.2514/6.2012-1812
Tuhaise, V. V., Handibry, J., and Abanda, F. H. 2023. Technologies for Digital Twin Applications in Construction. Automation in Construction. 152: 104931-104931. DOI: https://doi.org/10.1016/j.autcon.2023.104931
Vuoto, A., Funari, M. F., and Lourenço, P. B. 2023. On the Use of the Digital Twin Concept for the Structural Integrity Protection of Architectural Heritage. Infrastructures. 8(5): 86-86. DOI: https://doi.org/10.3390/infrastructures8050086
Ye, C., Kuok, S.-C., Butler, L. J., and Middleton, C. R. 2021. Implementing bridge model updating for operation and maintenance purposes: examination based on UK practitioners' views. Structure and Infrastructure Engineering. 18(12): 1638-1657. DOI: https://doi.org/10.1080/15732479.2021.1914115
Afzal, M., Yi, R., Shoaib, M., Muhammad Faisal Ayyub, Lavinia Chiara Tagliabue, Bilal, M., Ghafoor, H., and Manta, O. 2023. Delving into the Digital Twin Developments and Applications in the Construction Industry: A PRISMA Approach. Sustainability. 15(23): 16436-16436.
DOI: https://doi.org/10.3390/su152316436
Bunjaridh, Y., A. Rahman, R., and Mohamed Yusof, L. 2024. Digitalizing Construction - Key Organizational Capabilities for Digital Twin Production. Malaysia: Construction Industry Development Board (CIDB). https://smart.cidb.gov.my/article/digitalizing-construction-key-organizational-capabilities-for-digital-twin-production-385 Retrieved date: 2023, July 27
Mendes, N. 2023. BIM and Digital Twins in Infrastructure Projects: An overview from the Transportation Professional's Perspective. LSU Scholarly Repository. 5842. DOI: https://doi.org/10.31390/gradschool_theses.5842
Heaton, J., Parlikad, A. K., and Schooling, J. 2019. A Building Information Modelling approach to the alignment of organisational objectives to Asset Information Requirements. Automation in Construction. 104: 14-26. DOI: https://doi.org/10.1016/j.autcon.2019.03.022
Public Work Department (JKR). Department of Public Works Strategic Plan 2021-2025. 2022. Malaysia: Department of Public Works of Malaysia (Jabatan Kerja Raya / JKR) Global BIM Network. https://globalbim.org/info collection/department of public works strategic-plan-2021-2025/ Retrieved date: 2025, February 7
Senna, P., Cristina, B. A., Jaime, B. R., and Américo, A. 2023. Development of a digital maturity model for Industry 4.0 based on the technology-organization-environment framework. Computers & Industrial Engineering. 185: 109645-109645. DOI: https://doi.org/10.1016/j.cie.2023.109645
Qi, Q., Sui, F., Liu, A., Tao, F., Zhang, M., Song, B., Guo, Z., Lu, S. C.-Y., and Nee, A. Y. C. 2018. Digital twin-driven product design framework. International Journal of Production Research. 57(12): 3935-3953.
DOI: https://doi.org/10.1080/00207543.2018.1443229
Shahzad, M., Shafiq, M. T., Douglas, D., and Kassem, M. 2022. Digital Twins in Built Environments: An Investigation of the Characteristics, Applications, and Challenges. Buildings. 12(2): 120.DOI: https://doi.org/10.3390/buildings12020120
Xu, Y., Sun, Y., Liu, X., and Zheng, Y. (2019). A Digital-Twin-Assisted Fault Diagnosis Using Deep Transfer Learning. IEEE Access. 7: 19990-19999. DOI: https://doi.org/10.1109/access.2018.2890566
Opoku, D.-G. J., Perera, S., Osei-Kyei, R., Rashidi, M., Bamdad, K., and Famakinwa, T. 2023. Barriers to the Adoption of Digital Twin in the Construction Industry: A Literature Review. Informatics 2023. 10(1): 14. DOI: https://doi.org/10.3390/informatics10010014
Liu, M., Fang, S., Dong, H., and Xu, C. 2020. Review of Digital Twin about concepts, technologies, and Industrial Applications. Journal of Manufacturing Systems. 58: 346-361.
DOI: https://doi.org/10.1016/j.jmsy.2020.06.017
Zhong, D., Xia, Z., Zhu, Y., and Duan, J. 2023. Overview of predictive maintenance based on digital twin technology. Heliyon, 9(4): e14534.
DOI: https://doi.org/10.1016/j.heliyon.2023.e14534
Callcut, M., Cerceau Agliozzo, J.-P., Varga, L., and McMillan, L. (2021a). Digital Twins in Civil Infrastructure Systems. Sustainability, 13(20), 11549. DOI: https://doi.org/10.3390/su132011549
BizAdmin. 2024, October 22. Malaysia Construction Sector Achieve Remarkable Growth in 2024. Malaysia: Building & Investment. https://b i.info/malaysia construction sector achieve remarkable growth-in-2024/ Retrieved date: 2025, January 15
Uhlenkamp, J.-F., Hauge, J. B., Broda, E., Lutjen, M., Freitag, M., and Thoben, K.-D. 2022. Digital Twins: A Maturity Model for Their Classification and Evaluation. IEEE Access. 10: 69605–69635. DOI: https://doi.org/10.1109/access.2022.3186353.
Matchett, R., and Wium, J. 2017. Digital Twins For Road Infrastructure. 40th Southern African Transport Conference (SATC). 1-13. DOI:https://www.semanticscholar.org/paper/Digital-Twins-For-Road-Infrastructure Matchett Wium/5f830f1eae12f146d7a2693233ab0a78c79790d7
Liu, M., Fang, S., Dong, H., and Xu, C. 2020. Review of Digital Twin about concepts, technologies, and Industrial Applications. Journal of Manufacturing Systems. 58: 346-361. DOI: https://doi.org/10.1016/j.jmsy.2020.06.017
Errandonea, I., Beltrán, S., and Arrizabalaga, S. 2020. Digital Twin for maintenance: A literature review. Computers in Industry. 123: 103316.
DOI: https://doi.org/10.1016/j.compind.2020.103316
Yitmen, I., and Alizadehsalehi, S. Towards a Digital Twin-based Smart Built Environment. 2021. Florida: Taylor & Francis. 21–44. Retrieved date: 2024, July 22. DOI: https://doi.org/10.1201/9781003017547-2
Costin, A., Adibfar, A., Hu, H., and Chen, S. S. (2018). Building Information Modeling (BIM) for transportation infrastructure – Literature review, applications, challenges, and recommendations. Automation in Construction, 94, 257–281. DOI: https://doi.org/10.1016/j.autcon.2018.07.00
Sanfilippo, F., Thorstensen, R. T., Jha, A., Jiang, Z., and Robbersmyr, K. G. 2022. A perspective review on digital twins for roads, bridges, and civil infrastructures. 2022 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME). 1-6. DOI: https://doi.org/10.1109/iceccme55909.2022.9988693
Waqar, A., Othman, I., Almujibah, H., Khan, M. B., Alotaibi, S., and Elhassan, A. A. M. 2023. Factors Influencing Adoption of Digital Twin Advanced Technologies for Smart City Development: Evidence from Malaysia. Buildings. 13(3): 775. DOI: https://doi.org/10.3390/buildings13030775
Intan, N. A. S., and Doh , S. I. 2021. Factors Influencing Road Damage in Developing Countries. International Journal of Management Science and Engineering Research. 06(02). DOI: https://www.ijerm.com/vol/Volume-06-Issue-02 Retrieved date: 2023, August 27
Ismail, A., Razelan, I. S. M., Yusof, L. M., Zulkiple, A., and Masri, K. A. 2021. An Overview of Pavement Maintenance Management Strategies in Malaysia. IOP Conference Series: Earth and Environmental Science, 682(1): 012042. DOI: https://doi.org/10.1088/1755-1315/682/1/012042
Sehgal, S. 2023, March 9. Malaysia’s government eyes high spending. Malaysia: FrontierView. https://frontierview.com/insights/malaysias-government-eyes-high-spending/ Retrieved date: 2025, September 2
Lu, R., and Brilakis, I. 2019. Digital twinning of existing reinforced concrete bridges from labelled point clusters. Automation in Construction. 105: 102837. DOI: https://doi.org/10.1016/j.autcon.2019.102837













