Digital twin conceptual framework for the operation and maintenance phase in the building’s lifecycle

• Autorzy: Borkowski Andrzej Szymon

Identyfikatory

DOI

10.24425/ace.2024.150975

Warianty tytułu

PL

Ramy koncepcyjne cyfrowego bliźniaka dla fazy eksploatacji i konserwacji w cyklu życia budynku

• Języki publikacji: EN

Abstrakty

EN

AECO is struggling with data loss, inefficient processes and low productivity in asset management. The remedy to these problems seems to be the idea of Digital Twin (DT). However, the frameworks proposed so far do not always support a solution to these problems. This paper conducts an extensive literature review to develop a conceptual framework for the Operation and Maintenance (O&M) phase for building facilities. The conceptual framework takes into account the increasingly popular Internet of Things (IoT) and Artificial Intelligence (AI) technologies. The foundation, however, is Building Information Modeling (BIM) technology. The presented framework, after appropriate modifications, can also be applied to infrastructure facilities or city fragments. The paper presents limitations and directions for further research. The DT paradigm has been adopted and its adoption is ongoing. Its implementation will progress in the coming years. The advantages and benefits are certainly more numerous than the barriers and risks posed by the use of DT.

PL

Branża AECO zmaga się z utratą danych, nieefektywnymi procesami i niską produktywnością w zarządzaniu aktywami. Lekarstwem na te problemy wydaje się być idea cyfrowego bliźniaka (DT). Jednakże zaproponowane do tej pory ramy nie zawsze wspierają rozwiązanie tych problemów. W niniejszym artykule przeprowadzono obszerny przegląd literatury w celu opracowania ram koncepcyjnych dla fazy eksploatacji i konserwacji (O&M) obiektów kubaturowych. Ramy koncepcyjne uwzględniają coraz bardziej popularne technologie Internetu rzeczy (IoT) i sztucznej inteligencji (AI). Przedstawione ramy, po odpowiednich modyfikacjach, można również zastosować do obiektów infrastrukturalnych lub fragmentów miast. W artykule przedstawiono ograniczenia i kierunki dalszych badań. Paradygmat DT został przyjęty i jego wdrażanie jest w toku. Jego adopcja będzie postępować w nadchodzących latach.

Słowa kluczowe

EN

digital twin; conceptual framework; operation; maintenance; building information modelling; internet of things

PL

bliźniak cyfrowy; ramy koncepcyjne; eksploatacja; konserwacja; modelowanie informacji o budynku; internet rzeczy

• Wydawca: Komitet Inżynierii Lądowej i Wodnej PAN ; Politechnika Warszawska, Wydział Inżynierii Lądowej
• Czasopismo: Archives of Civil Engineering
• Rocznik: 2024
• Tom: Vol. 70, nr 3
• Strony: 139--152
• Opis fizyczny: Bibliogr. 57 poz., il.

Twórcy

autor

Borkowski Andrzej Szymon

• Warsaw University of Technology, Faculty of Geodesy and Cartography, Warsaw, Poland

• https://orcid.org/0000-0002-7013-670X

Bibliografia

• [1] A.S. Borkowski, “Evolution of BIM: epistemology, genesis and division into periods”, Journal of Information Technology in Construction, vol. 28, pp. 646-661, 2023, doi: 10.36680/j.itcon.2023.034.
• [2] A. Prabhakaran, A.M. Mahamadu, L. Mahdjoubi, J. Andric, P. Manu, and D. Mzyece, “An investigation into macro BIM maturity and its impacts: a comparison of Qatar and the United Kingdom”, Architectural Engineering and Design Management, vol. 17, no. 5-6, pp. 496-515, 2021, doi: 10.1080/17452007.2021.1923454.
• [3] E. Troiani, A. M. Mahamadu, P. Manu, E. Kissi, C. Aigbavboa, and A. Oti, “Macro-maturity factors and their influence on micro-level BIM implementation within design firms in Italy”, Architectural Engineering and Design Management, vol. 16, no. 3, pp. 209-226, 2020, doi: 10.1080/17452007.2020.1738994.
• [4] H. V. Catapult, “Untangling the requirements of a digital twin”, University of Sheffield Advanced Manufacturing Research Centre (AMRC), 2021.
• [5] H. Boyes and T. Watson, “Digital twins: An analysis framework and open issues”, Computers in Industry, vol. 143, art. no. 103763, 2022, doi: 10.1016/j.compind.2022.103763.
• [6] A. Schweigkofler, O. Braholli, S. Akro, et al., “Digital Twin as energy management tool through IoT and IM data integration”, in CLIMA 2022 conference. Rotterdam, 2022, doi: 10.34641/clima.2022.46.
• [7] T. Erol, A.F. Mendi, and D. Dogan, “Digital transformation revolution with digital twin technology”, in 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT). Istanbul, 2020, pp. 1-7, doi: 10.1109/ISMSIT50672.2020.9254288.
• [8] J.M.D. Delgado and L. Oyedele, “Digital Twins for the built environment: learning from conceptual and process models in manufacturing”, Advanced Engineering Informatics, vol. 49, 101332, 2021, doi: 10.1016/j.aei.2021.101332.
• [9] V.V. Lehtola, M. Koeva, S.O. Elberink, P. Raposo, J. P. Virtanen, F. Vahdatikhaki, and S. Borsci, “Digital twin of a city: Review of technology serving city needs”, International Journal of Applied Earth Observation and Geoinformation, vol. 114, art. no. 102915, 2022, doi: 10.1016/j.jag.2022.102915.
• [10] M. Baghalzadeh Shishehgarkhaneh, A. Keivani, R.C. Moehler, N. Jelodari, and S. Roshdi Laleh, “Internet of Things (IoT), Building Information Modeling (BIM), and Digital Twin (DT) in construction industry: A review, bibliometric, and network analysis”, Buildings, vol. 12, no. 10, art. no. 1503, 2022, doi: 10.3390/buildings12101503.
• [11] S. Esser, S.Vilgertshofer, and A. Borrmann, “A reference framework enabling temporal scalability of object-based synchronization in BIM Level 3 systems”, presented at European Conference on Computing in Construction, 40th International CIB W78 Conference, 10-12 July 2023, Heraklion, Crete, Greece, 2023.
• [12] A.S. Borkowski, Ł. Kochański, and M. Wyszomirski, “A Case Study on Building Information (BIM) and Land Information (LIM) Models Including Geospatial Data”, Geomatics and Environmental Engineering, vol. 17, no. 1, pp. 19-34, 2023, doi: 10.7494/geom.2023.17.1.19.
• [13] M. Szóstak and M. Napiórkowski, “Virtual reality in construction safety training – fears and expectations”, Builder, vol. 308, pp. 16-19, 2023, doi: 10.5604/01.3001.0016.2680.
• [14] C. Boje, A. Guerriero, S. Kubicki, and Y. Rezgui, “Towards a semantic Construction Digital Twin: Directions for future research”, Automation in Construction, vol. 114, art. no. 103179, 2020, doi: 10.1016/j.autcon.2020.103179.
• [15] S. Honghong, Y. Gang, L. Haijiang, Z. Tian, and J. Annan, “Digital twin enhanced BIM to shape full life cycle digital transformation for bridge engineering”, Automation in Construction, vol. 147, art. no. 104736, 2023, doi: 10.1016/j.autcon.2022.104736.
• [16] F. Jiang, L. Ma, T. Broyd, and K. Chen, “Digital twin and its implementations in the civil engineering sector”, Automation in Construction, vol. 130, art. no. 103838, 2021, doi: 10.1016/j.autcon.2021.103838.
• [17] C. Chen, Z. Zhao, J. Xiao, and R. Tiong, “A conceptual framework for estimating building embodied carbon based on digital twin technology and life cycle assessment”, Sustainability, vol. 13, no. 24, art. no. 13875, 2021, doi: 10.3390/su132413875.
• [18] C. Ye, L. Butler, B. Calka, et al., “A digital twin of bridges for structural health monitoring”, in 12th International Workshop on Structural Health Monitoring 2019. Stanford University, 2019, doi: 10.17863/CAM.63903.
• [19] M. Mohammadi, M. Rashidi, Y. Yu, and B. Samali, “Integration of TLS-derived Bridge Information Modeling (BrIM) with a Decision Support System (DSS) for digital twinning and asset management of bridge infrastructures”, Computers in Industry, vol. 147, art. no. 103881, 2023, doi: 10.1016/j.compind.2023.103881.
• [20] B. Fecher, S. Friesike, and M. Hebing, “What drives academic data sharing”, PloS one, vol. 10, art. no. e0118053, 2015, doi: 10.1371/journal.pone.0118053.
• [21] J. Zhao, H. Feng, Q. Chen, and B.G. de Soto, “Developing a conceptual framework for the application of digital twin technologies to revamp building operation and maintenance processes”, Journal of Building Engineering, vol. 49, art. no. 104028, 2022, doi: 10.1016/j.jobe.2022.104028.
• [22] T.F. Søndergaard, J. Andersen, and B. Hjørland, “Documents and the communication of scientific and scholarly information: Revising and updating the UNISIST model”, in Proceedings of the American Society for Information Science and Technology, vol. 40, no. 1, pp. 516-516, 2003, doi: 10.1002/meet.14504001102.
• [23] G.B. Ozturk, “Digital twin research in the AECO-FM industry”, Journal of Building Engineering, vol. 40, art. no. 102730, 2021, doi: 10.1016/j.jobe.2021.102730.
• [24] A.Z.A.O. Al-Hijazeen, M. Fawad, M. Gerges, K. Koris, and M. Salamak, “Implementation of digital twin and support vector machine in structural health monitoring of bridges”, Archives of Civil Engineering, vol. 69, no. 3, pp. 31-47, 2023, doi: 10.24425/ace.2023.146065.
• [25] W. Koperska, M. Stachowiak, N. Duda-Mróz, P. Stefaniak, B. Jachnik, B. Bursa, and P. Stefanek, “The Tailings Storage Facility (TSF) stability monitoring system using advanced big data analytics on the example of the Zelazny Most Facility”, Archives of Civil Engineering, vol. 68, no. 2, pp. 297-311, 2022, doi: 10.24425/ace.2022.140643.
• [26] Q. Lu, X. Xie, A.K. Parlikad, J.M. Schooling, and E. Konstantinou, “Moving from building information models to digital twins for operation and maintenance”, Proceedings of the Institution of Civil Engineers-Smart Infrastructure and Construction, vol. 174, no. 2, pp. 46-56, 2021, doi: 10.1680/jsmic.19.00011.
• [27] X. Zhang, J. Shen, P.K. Saini, M. Lovati, M. Han, P. Huang, and Z. Huang, “Digital twin for accelerating sustainability in positive energy districts: A review of simulation tools and applications”, Frontiers in Sustainable Cities, vol. 3, art. no. 663269, 2021, doi: 10.3389/frsc.2021.663269.
• [28] J.A. Torrecilla-García, M.C. Pardo-Ferreira, and J.C. Rubio-Romero, “Overall introduction to the framework of BIM-based digital twinning in decision-making in safety management in building construction industry”, Direccion y Organizacion, vol. 74, pp. 31-38, 2021, doi: 10.37610/dyo.v0i74.600.
• [29] M. Deng, C.C. Menassa, and V.R. Kamat, “From BIM to digital twins: A systematic review of the evolution of intelligent building representations in the AEC-FM industry”, Journal of Information Technology in Construction, vol. 26, pp. 58-83, 2021, doi: 10.36680/j.itcon.2021.005.
• [30] Y. Jiang and H. Chen, “Intelligent building construction management based on BIM digital twin”, Computational Intelligence and Neuroscience, vol. 2021, pp. 1-11, 2021, doi: 10.1155/2021/4979249.
• [31] H. Sun and Z. Liu, “Research on intelligent dispatching system management platform for construction projects based on digital Twin and BIM technology”, Advances in Civil Engineering, vol. 2022, pp. 1-9, 2022, doi: 10.1155/2022/8273451.
• [32] R. Klinc and Ž. Turk, “Construction 4.0-digital transformation of one of the oldest industries”, Economic and Business Review, vol. 21, no. 3, 2019, doi: 10.15458/ebr.92.
• [33] Q.J.Wen, Z.J. Ren, H. Lu, and J.F.Wu, “The progress and trend of BIM research: A bibliometrics-based visualization analysis”, Automation in Construction, vol. 124, art. no. 103558, 2021, doi: 10.1016/j.autcon.2021.103558.
• [34] N.A. Megahed and A.M. Hassan, “Evolution of BIM to DTs: A Paradigm Shift for the Post-Pandemic AECO Industry”, Urban Science, vol. 6, no. 4, 2022, doi: 10.3390/urbansci6040067.
• [35] M.M. Abdelrahman, A. Chong, and C. Miller, “Personal thermal comfort models using digital twins: Preference prediction with BIM-extracted spatial-temporal proximity data from Build2Vec”, Building and Environment, vol. 207, art. no. 108532, 2022, doi: 10.1016/j.buildenv.2021.108532.
• [36] Y. Pan and L. Zhang, “A BIM-data mining integrated digital twin framework for advanced project management”, Automation in Construction, vol. 124, art. no. 103564, 2021, doi: 10.1016/j.autcon.2021.103564.
• [37] S.H. Khajavi, N.H. Motlagh, A. Jaribion, L.C. Werner, and J. Holmström, “Digital twin: vision, benefits, boundaries, and creation for buildings”, IEEE Access, vol. 7, pp. 147406-147419, 2019, doi: 10.1109/ACCESS.2019.2946515.
• [38] T. Wang, V.J. Gan, D. Hu, and H. Liu, “Digital twin-enabled built environment sensing and monitoring through semantic enrichment of BIM with SensorML”, Automation in Construction, vol. 144, art. no. 104625, 2022, doi: 10.1016/j.autcon.2022.104625.
• [39] Q. Lu, X. Xie, J. Heaton, A.K. Parlikad, and J. Schooling, “From BIM towards digital twin: strategy and future development for smart asset management. Service Oriented, Holonic and Multi-agent Manufacturing Systems for Industry of the Future”, in Proceedings of SOHOMA 2019, vol. 9. Springer, 2020, pp. 392-404, doi: 10.1007/978-3-030-27477-1_30.
• [40] C. Rausch, B. Sanchez, M.E. Esfahani, and C. Haas, “Computational algorithms for digital twin support in construction”, in Construction Research Congress 2020. Reston, VA: American Society of Civil Engineers, 2020, pp. 191-200, doi: 10.1061/9780784482865.021.
• [41] A. Karmakar and V.S.K. Delhi, “Construction 4.0: what do we know and where are we headed?”, Journal of Information Technology in Construction, vol. 26, pp. 526-545, 2021, doi: 10.36680/j.itcon.2021.028.
• [42] K. Afsari, C.M. Eastman, and D.R. Shelden, “Cloud-based BIM data transmission: current status and challenges. In ISARC”, in Proceedings of the International Symposium on Automation and Robotics in Construction. IAARC Publications, vol. 33, 2016.
• [43] Y. Tan, P. Chen, W. Shou, and A. M. Sadick, “Digital Twin-driven approach to improving energy efficiency of indoor lighting based on computer vision and dynamic BIM”, Energy and Buildings, vol. 270, art. no. 112271, 2022, doi: 10.1016/j.enbuild.2022.112271.
• [44] P. Hagedorn, L. Liu, M. König, et al., “BIM-Enabled Infrastructure Asset Management Using Information Containers and Semantic Web”, Journal of Computing in Civil Engineering, vol. 37, no. 1, art. no. 04022041, 2023, doi: 10.1061/(ASCE)CP.1943-5487.0001051.
• [45] A.S. Bale, N. Ghorpade, M.F. Hashim, J. Vaishnav, and Z. Almaspoor, “A comprehensive study on Metaverse and its impacts on humans”, Advances in Human-Computer Interaction, vol. 2022, pp. 1-11, 2022, doi: 10.1155/2022/3247060.
• [46] S.M. Sepasgozar, “Differentiating digital twin from digital shadow: Elucidating a paradigm shift to expedite a smart, sustainable built environment”, Buildings, vol. 11, no. 4, 2021, doi: 10.3390/buildings11040151.
• [47] W. Kritzinger, M. Karner, G. Traar, J. Henjes, and W. Sihn, “Digital Twin in manufacturing: A categorical literature review and classification”, Ifac-PapersOnline, vol. 51, no. 11, pp. 1016-1022, 2018, doi: 10.1016/j.ifacol.2018.08.474.
• [48] M. El Jazzar, M. Piskernik, and H. Nassereddine, “Digital twin in construction: An empirical analysis”, in EG-ICE 2020 Workshop on Intelligent Computing in Engineering, Proceedings. 2020, pp. 501-510.
• [49] Y. Peng, M. Zhang, F. Yu, J. Xu, and S. Gao, “Digital twin hospital buildings: an exemplary case study through continuous lifecycle integration”, Advances in Civil Engineering, vol. 2020, pp. 1-13, 2020, doi: 10.1155/2020/8846667.
• [50] A. Arsiwala, F. Elghaish, and M. Zoher, “Digital twin with Machine learning for predictive monitoring of CO2 equivalent from existing buildings”, Energy and Buildings, vol. 284, art. no. 112851, 2023, doi: 10.1016/j.enbuild.2023.112851.
• [51] Ž. Turk, “Interoperability in construction-Mission impossible?”, Developments in the Built Environment, vol. 4, art. no. 100018, 2020, doi: 10.1016/j.dibe.2020.100018.
• [52] M. Almatared, H. Liu, S. Tang, M. Sulaiman, Z. Lei, and H.X. Li, “Digital twin in the architecture, engineering, and construction industry: A bibliometric review”, in Construction Research Congress 2022. ASCE, 2022, pp. 670-678, doi: 10.1061/9780784483961.070.
• [53] H.H. Hosamo, A. Imran, J. Cardenas-Cartagena, P.R. Svennevig, K. Svidt, and H.K. Nielsen, “A review of the digital twin technology in the AEC-FM industry”, Advances in Civil Engineering, vol. 2022, pp. 1-17, 2022, doi: 10.1155/2022/2185170.
• [54] L. Doumbouya, G. Gao, and C. Guan, “Adoption of the Building Information Modeling (BIM) for construction project effectiveness: The review of BIM benefits”, American Journal of Civil Engineering and Architecture, vol. 4, no. 3, pp. 74-79, 2016, doi: 10.12691/ajcea-4-3-1.
• [55] K. Zima and E. Mitera-Kiełbasa, “Level of Information Need for BIM Models: Australia, New Zealand and ISO 19650”, Civil And Environmental Engineering Reports, vol. 32, no. 4, pp. 1-12, 2022, doi: 10.2478/ceer-2022-0041.
• [56] A. Flamini, R. Loggia, A. Massaccesi, C. Moscatiello, and L. Martirano, “BIM and SCADA integration: the Dynamic Digital Twin”, in 2022 IEEE/IAS 58th Industrial and Commercial Power Systems Technical Conference (I&CPS). IEEE, 2022, pp. 1-7, doi: 10.1109/ICPS54075.2022.9773903.
• [57] A. Glema, “Building information modeling BIM-level of digital construction”, Archives of Civil Engineering, vol. 63, no. 3, pp. 39-51, 2017, doi: 10.1515/ace-2017-0027.