Gestão & Produção
Gestão & Produção
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Digital twins as enablers of structure inspection and maintenance

Julia Menegon; Eduardo Luís Isatto

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Abstract:: The emergence of new technologies based on the exchange of data and information via the internet has prompted a revolution in the industry as a whole. First applied in manufacturing, the movement known as the Fourth Industrial Revolution soon spread and changed the dynamics of many other fields. Digital twins (DTs), one of the technologies that emerged in this scenario, are used to replicate physical environments in virtual models. Such models must be supplied with up-to-date information throughout a product's lifecycle to ensure accurate representation of the real asset. DTs have great potential to impact the construction industry, supporting facilities management, simulation tasks, and centralized management and recording of interventions. However, despite the attention the theme has attracted among researchers and companies, implementation of the concept in practical situations is still largely underexplored. Thus, this study aims to critically analyze the concept of DTs and their potential in the construction industry, particularly in inspection and maintenance tasks for existing structures. The study comprises a literature review undertaken to identify the multiple types of DT models, examine barriers and opportunities associated with their use, and discuss their potential as enablers of inspection and maintenance strategies. Furthermore, research opportunities related to the use of DTs for structural inspection and maintenance are suggested.


Digital twin, Construction, BIM, Inspection, Maintenance of structures


Ali, A. M., Mohamed, E., Yacout, S., & Shaban, Y. (2020). Cloud computing based unsupervised fault diagnosis system in the context of Industry 4.0. Gestão & Produção, 27(3), e5378.

Angjeliu, G., Coronelli, D., & 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.

Associação Brasileira de Normas Técnicas - ABNT. (2012). NBR 5674: Manutenção de Edificações - Requisitos para o sistema de gestão de manutenção. Rio de Janeiro: ABNT.

Davila Delgado, J. M., & Oyedele, L. (2021). Digital Twins for the built environment: learning from conceptual and process models in manufacturing. Advanced Engineering Informatics, 49, 101332.

Eastman, C., Teicholz, P., Sacks, R., & Liston, K. (2011). BIM handbook: a guide to building information modeling for owners, managers, designers, engineers and contractors (2nd ed.). Hoboken: Wiley.

Errandonea, I., Beltrán, S., & Arrizabalaga, S. (2020). Digital Twin for maintenance: a literature review. Computers in Industry, 123, 103316.

Ferreira, F. M. C., & Souza, H. A. (2021). Management for maintenance of public education. Gestão & Produção, 28(1), 1-17.

Firmino, A. S., Perles, G. X., Mendes, J. V., Silva, J. E. A. R., & Silva, D. A. L. (2020). Towards Industry 4.0: a SWOT-based analysis for companies located in the Sorocaba Metropolitan Region (São Paulo State, Brazil). Gestão & Produção, 27(3), 1-21.

Glaessgen, E. H., & Stargel, D. S. (2012). The digital twin paradigm for future NASA and U.S. Air force vehicles. In Collection of Technical Papers - AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference (pp. 1-14). Reston, VA: AIAA.

Grieves, M., & Vickers, J. (2016). Digital twin: mitigating unpredictable, undesirable emergent behavior in complex systems. In J. Kahlen, S. Flumerfelt & A. Alves (Eds.), Transdisciplinary perspectives on complex systems (pp. 85-113). Cham: Springer.

Isailović, D., Stojanovic, V., Trapp, M., Richter, R., Hajdin, R., & Döllner, J. (2020). Bridge damage: detection, IFC-based semantic enrichment and visualization. Automation in Construction, 112, 103088.

Jiang, F., Ma, L., Broyd, T., & Chen, K. (2021). Digital twin and its implementations in the civil engineering sector. Automation in Construction, 130, 103838.

Kritzinger, W., Karner, M., Traar, G., Henjes, J., & Sihn, W. (2018). Digital Twin in manufacturing: a categorical literature review and classification. IFAC-PapersOnLine, 51(11), 1016-1022.

Lasi, H., Fettke, P., Kemper, H.-G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & Information Systems Engineering, 6(4), 239-242.

Lin, K., Xu, Y. L., Lu, X., Guan, Z., & Li, J. (2021). Digital twin-based collapse fragility assessment of a long-span cable-stayed bridge under strong earthquakes. Automation in Construction, 123, 103547.

Lu, R., & Brilakis, I. (2019). Digital twinning of existing reinforced concrete bridges from labelled point clusters. Automation in Construction, 105, 102837.

Mesquita, E., Arêde, A., Pinto, N., Antunes, P., & Varum, H. (2018). Long-term monitoring of a damaged historic structure using a wireless sensor network. Engineering Structures, 161, 108-117.

Morgenthal, G., Hallermann, N., Kersten, J., Taraben, J., Debus, P., Helmrich, M., & Rodehorst, V. (2019). Framework for automated UAS-based structural condition assessment of bridges. Automation in Construction, 97, 77-95.

Moyano, J., Gil-Arizón, I., Nieto-Julián, J. E., & Marín-García, D. (2021). Analysis and management of structural deformations through parametric models and HBIM workflow in architectural heritage. Journal of Building Engineering, 45, 103274.

Opoku, D. G. J., Perera, S., Osei-Kyei, R., & Rashidi, M. (2021). Digital twin application in the construction industry: a literature review. Journal of Building Engineering, 40, 102726.

Ozturk, G. B. (2021). Digital Twin Research in the AECO-FM industry. Journal of Building Engineering, 40, 102730.

Park, K. T., Lee, D., & Do Noh, S. (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.

Silva, J. F., Silva, F. L., Silva, D. O., Rocha, L. A. O., & Ritter, Á. M. (2022). Decision making in the process of choosing and deploying industry 4.0 technologies. Gestão & Produção, 29, e163.

Tao, F., & Zhang, M. (2017). Digital Twin Shop-Floor: a new shop-floor paradigm towards smart manufacturing. IEEE Access: Practical Innovations, Open Solutions, 5, 10.

Tao, F., Zhang, M., Liu, Y., & Nee, A. Y. C. (2018). Digital twin driven prognostics and health management for complex equipment. CIRP Annals - Manufacturing Technology, 67(1), 169-172.

Tavares, L. (2020). Masterclass Gêmeos Digitais - O Impacto da próxima disrupção pós BIM. Retrieved in 2022, January 13, from

Wohlin, C. (2014). Guidelines for snowballing in systematic literature studies and a replication in software engineering. In ACM International Conference Proceeding Series. New York: ACM.

Zhao, S., Kang, F., Li, J., & Ma, C. (2021). Structural health monitoring and inspection of dams based on UAV photogrammetry with image 3D reconstruction. Automation in Construction, 130, 103832.

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