Cited by 609BIM and Construction IntegrationDigital Transformation in IndustryConstruction Management and Sustainability

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 access

Abstract

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.

Overview

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Registry

Crossref · 10.1017/dce.2020.16

Cites

88 of 88 references verified0 citation errors · 0 not checkable

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Citations

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Show all 91 references

3 of the 91 references couldn’t be matched to a known paper.

Research works printed but not linked: 8

  1. Fujimoto, 2019, Key Concepts for Improving Supply Chain Robustness (Number 511; Discussion Paper Series, p. 21)
  2. Whyte, J , Fitzgerald, J , Mayfield, M , Coca, D , Pierce, K and Shah, N (2019) Projects as Interventions in Infrastructure Systems-of-systems, International Committee on Systems Engineering (INCOSE) International Symposium 2019, July 20–25, Orlando, USA.
  3. 2016, Virtual Construction 2007
  4. Bolton, 2018, Gemini Principles
  5. Eastman, 2011, BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Architects, Engineers, Contractors, and Fabricators
  6. Steup, 2018, The Stanford Encyclopedia of Philosophy
  7. Laudan, 1978, Progress and Its Problems: Towards a Theory of Scientific Growth, 282
  8. Floridi, 2019, The Stanford Encyclopedia of Philosophy

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Items 401–500 of 609

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
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
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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