The DOI matches its Crossref record; 88 of the 91 references it cites were found in a registry or an index.
Construction with digital twin information systems
Open accessAbstract
The concept of a “digital twin” as a model for data-driven management and control of physical systems has emerged over the past decade in the domains of manufacturing, production, and operations. In the context of buildings and civil infrastructure, the notion of a digital twin remains ill-defined, with little or no consensus among researchers and practitioners of the ways in which digital twin processes and data-centric technologies can support design and construction. This paper builds on existing concepts of Building Information Modeling (BIM), lean project production systems, automated data acquisition from construction sites and supply chains, and artificial intelligence to formulate a mode of construction that applies digital twin information systems to achieve closed loop control systems. It contributes a set of four core information and control concepts for digital twin construction (DTC), which define the dimensions of the conceptual space for the information used in DTC workflows. Working from the core concepts, we propose a DTC information system workflow—including information stores, information processing functions, and monitoring technologies—according to three concentric control workflow cycles. DTC should be viewed as a comprehensive mode of construction that prioritizes closing the control loops rather than an extension of BIM tools integrated with sensing and monitoring technologies.
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In the citing paper
“Improved management and outcomes through digital twin integration”
From Advancing civil infrastructure with digital twins: a review of applications and challenges (2025) · cites this paper as Sacks et al. (2020)
Citations
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“Although there is no commonly agreed conceptualization or definition of the term (Kritzinger et al., 2018; Gerber et al., 2019), numerous organizations have defined digital twins in terms of their functions and characteristics.”
BackgroundStanford Encyclopedia of Philosophy
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“This idea has spawned broad areas of research, such as Automated Project Performance Control (APPC) (Navon and Sacks, 2007), Construction 4.0 (Oesterreich and Teuteberg, 2016), and construction applications of technologies for acquisition of as-built geometry, including, for example, photogrammetry…”
BackgroundInfluentialTowards a semantic Construction Digital Twin: Directions for future research
Boje, C., Guerriero, A., Kubicki, S., & Rezgui, Y. (2020) · Automation in Construction · doi:10.1016/j.autcon.2020.103179 · Cited by 1,477
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“…and virtual counterparts, enabled by the development of advanced sensing (e.g., computer vision), internet of things (e.g., interconnected assets), high-speed networking (e.g., 5G internet), and advanced analytics (e.g., machine learning) technologies (Rosen et al., 2015; Gerber et al., 2019).”
BackgroundInfluentialApplication of the New Production Philosophy to Construction
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Cited by
Sorted by citations
Digital twin: benefits, use cases, challenges, and opportunities
Attaran, M., & Celik, B. G. (2023) · Decision Analytics Journal · doi:10.1016/j.dajour.2023.100165 · Cited by 704
Digital twin application in the construction industry: A literature review
Opoku, D.-G. J., Perera, S., Osei-Kyei, R., & Rashidi, M. (2021) · Journal of Building Engineering · doi:10.1016/j.jobe.2021.102726 · Cited by 753
Digital Twin applications toward Industry 4.0: A Review
Javaid, M., Haleem, A., & Suman, R. (2023) · Cognitive Robotics · doi:10.1016/j.cogr.2023.04.003 · Cited by 466
Shahzad, M., Shafiq, M. T., Douglas, D., & Kassem, M. (2022) · Buildings · doi:10.3390/buildings12020120 · Cited by 356
Delgado, J. M. D., & Oyedele, L. O. (2021) · Advanced Engineering Informatics · doi:10.1016/j.aei.2021.101332 · Cited by 272
Metadata
- Authors
- Sacks, R., Brilakis, I., Pikas, E., Xie, H. S., & Girolami, M.
- Affiliations
- Technion – Israel Institute of Technology (IL)
- University of Cambridge (GB)
- Aalto University (FI)
- Corresponding author
- Sacks, Rafael
- Venue
- Data-Centric Engineering
- Publisher
- Cambridge University Press (CUP)
- Published
- 2020
- Volume
- 1
- ISSN
- 2632-6736 (ISSN-L)
- OpenAlex
- W3107782157
- Cited by
- 609
- References
- 91
- Citations by year
- 2026: 133 · 2025: 129 · 2024: 128 · 2023: 106 · 2022: 73 · 2021: 40
- FWCI
- 29.01
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Data-Centric Engineering (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Cambridge University Engineering Department Publications Database (submittedVersion)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Apollo (cc-by)
- Funders
- Department for Business, Energy and Industrial Strategy, UK Government
- UK Research and Innovation
- University of Cambridge
- Engineering and Physical Sciences Research Council (EP/R034710/1)
- Innovate UK
- Topics
- Physical Sciences › Engineering › Building and Construction › BIM and Construction Integration
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Engineering › Building and Construction › Construction Management and Sustainability
- Keywords
- digital twin, construction, building information modeling, lean construction, feedback control, construction information systems, construction monitoring, data acquisition, artificial intelligence in construction, civil infrastructure
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