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Journal ArticleDOI

Digital twin application in the construction industry: A literature review

TL;DR: In this paper, the authors comprehensively reviewed and analyzed digital twin (DT) concept, technologies, and application in the construction industry using a systematic review methodology while incorporating the science mapping method.
Abstract: The construction industry is faced with numerous challenges including low productivity, lack of research and development, and poor technology advancements . Advances in digital technologies such as digital twin (DT) has seen enormous utilisations in digitally advanced industries including the manufacturing and automotive industries. It presents an opportunity for the integration of the physical world to the digital world. DT technology has the potential to transform the construction industry and provide responses to some of its challenges. As a result, the concept of DT has attracted much attention and is developing at a rapid pace. The overarching aim of this study was to analyse the current state of DT applications in the construction industry. This study comprehensively reviews and analyses DT concept, technologies, and application in the construction industry using a systematic review methodology while incorporating the science mapping method. After a complete search of several databases and careful selection in line with the proposed criteria, 22 academic publications about DT application in the construction industry were identified and classified accordingly. The research analysed in detail the status, evolution of the concept, key technologies, and six areas of application in the lifecycle phases of a project: building information modeling , structural system integrity, facilities management, monitoring, logistics processes, and energy simulation. This research shows that there is a high potential for DT to enable solutions to the numerous challenges in the construction industry. Thus, this study raises the level of awareness and need for the application of DT in the construction industry.
Citations
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Journal ArticleDOI
TL;DR: In this paper, the authors organize the existing studies on DTs with a focus on barriers and enablers, and propose conceptual models describing enabler of and barrier to DT implementation, as well as their mutual relationships.

49 citations

Journal ArticleDOI
TL;DR: In this article, the authors provide a comprehensive methodology along with a thorough bridge case study to evaluate two digital point clouds developed from an existing Australian heritage bridge via both UAV-based photogrammetry and TLS.
Abstract: In the current modern era of information and technology, emerging remote advancements have been widely established for detailed virtual inspections and assessments of infrastructure assets, especially bridges. These technologies are capable of creating an accurate digital representation of the existing assets, commonly known as the digital twins. Digital twins are suitable alternatives to in-person and on-site based assessments that can provide safer, cheaper, more reliable, and less distributive bridge inspections. In the case of bridge monitoring, Unmanned Aerial Vehicle (UAV) photogrammetry and Terrestrial Laser Scanning (TLS) are among the most common advanced technologies that hold the potential to provide qualitative digital models; however, the research is still lacking a reliable methodology to evaluate the generated point clouds in terms of quality and geometric accuracy for a bridge size case study. Therefore, this paper aims to provide a comprehensive methodology along with a thorough bridge case study to evaluate two digital point clouds developed from an existing Australian heritage bridge via both UAV-based photogrammetry and TLS. In this regard, a range of proposed approaches were employed to compare point clouds in terms of points’ distribution, level of outlier noise, data completeness, surface deviation, and geometric accuracy. The comparative results of this case study not only proved the capability and applicability of the proposed methodology and approaches in evaluating these two voluminous point clouds, but they also exhibited a higher level of point density and more acceptable agreements with as-is measurements in TLS-based point clouds subjected to the implementation of a precise data capture and a 3D reconstruction model.

35 citations

Journal ArticleDOI
TL;DR: In this paper , an overview of the implementation of DT technology in electric vehicles (EV) propulsion drive systems is presented, supplemented with main applications analysis and comparison between different simulation technologies.
Abstract: The significant progress in the electric automotive industry brought a higher need for new technological innovations. Digital Twin (DT) is one of the hottest trends of the fourth industrial revolution. It allows representing physical assets under various operating conditions in a low-cost and zero-risk environment. DTs are used in many different fields from aerospace to healthcare. However, one of the perspective applications of such technology is the automotive industry. This paper presents an overview of the implementation of DT technology in electric vehicles (EV) propulsion drive systems. A general review of DT technology is supplemented with main applications analysis and comparison between different simulation technologies. Primary attention is given to the adaptation of DT technology for EV propulsion drive systems.

31 citations

Journal ArticleDOI
TL;DR: Wang et al. as discussed by the authors designed a fault identification and chopping algorithm based on deep neural network (AL-DNN) and domain adversarial neural networks (DANN), and a digital twins workshop management and control system is designed for intelligent manufacturing.
Abstract: In this article, the proposed work aims to further optimize the fault diagnosis effect of manufacturing equipment, explore the application of digital twins technology in intelligent manufacturing. The equipment failures in Poka Yoke technology are adopted, and a fault identification and chopping algorithm is designed based on the active learning—deep neural network (AL-DNN) and domain adversarial neural networks (DANN). In addition, a digital twins workshop management and control system is designed for intelligent manufacturing management. The experimental exploration reveals that the accuracy of the AL-DNN algorithm is as high as 99.248%, which is more in line with practical applications. The DANN algorithm can realize fault identification and diagnosis under different working conditions. Compared with other deep learning algorithms, the accuracy of the DANN can be increased by up to 20.256%, showing higher accuracy in contrast to the traditional algorithm, so the effect is more stable. In addition, the digital twins manufacturing management system designed shows good performances, which can intuitively display the specific conditions of workshop and realize basic operating functions. The concept of digital twins is innovatively introduced into equipment fault diagnosis and trend prediction, which can provide scientific and effective reference data for subsequent research on intelligent manufacturing.

27 citations

Journal ArticleDOI
TL;DR: The applications of DT in 13 different industries including the manufacturing, agriculture, education, construction, medicine, and retail, along with the industrial use case in these industries are covered.
Abstract: One of the most promising technologies that is driving digitalization in several industries is Digital Twin (DT). DT refers to the digital replica or model of any physical object (physical twin). What differentiates DT from simulation and other digital or CAD models is the automatic bidirectional exchange of data between digital and physical twins in real-time. The benefits of implementing DT in any sector include reduced operational costs and time, increased productivity, better decision making, improved predictive/preventive maintenance, etc. As a result, its implementation is expected to grow exponentially in the coming decades as, with the advent of Industry 4.0, products and systems have become more intelligent, relaying on collection and storing incremental amounts of data. Connecting that data effectively to DTs can open up many new opportunities and this paper explores different industrial sectors where the implementation of DT is taking advantage of these opportunities and how these opportunities are taking the industry forward. The paper covers the applications of DT in 13 different industries including the manufacturing, agriculture, education, construction, medicine, and retail, along with the industrial use case in these industries.

26 citations

References
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Journal Article
TL;DR: A review of prior, relevant literature is an essential feature of any academic project that facilitates theory development, closes areas where a plethora of research exists, and uncovers areas where research is needed.
Abstract: A review of prior, relevant literature is an essential feature of any academic project. An effective review creates a firm foundation for advancing knowledge. It facilitates theory development, closes areas where a plethora of research exists, and uncovers areas where research is needed.

6,406 citations

Journal ArticleDOI
TL;DR: This paper proposes a unique open-source tool, designed by the authors, called bibliometrix, for performing comprehensive science mapping analysis, programmed in R, and can be rapidly upgraded and integrated with other statistical R-packages.

3,502 citations

Journal ArticleDOI
TL;DR: The content coverage and practical utility of PubMed, Scopus, Web of Science, and Google Scholar are compared and PubMed remains an optimal tool in biomedical electronic research.
Abstract: The evolution of the electronic age has led to the development of numerous medical databases on the World Wide Web, offering search facilities on a particular subject and the ability to perform citation analysis. We compared the content coverage and practical utility of PubMed, Scopus, Web of Science, and Google Scholar. The official Web pages of the databases were used to extract information on the range of journals covered, search facilities and restrictions, and update frequency. We used the example of a keyword search to evaluate the usefulness of these databases in biomedical information retrieval and a specific published article to evaluate their utility in performing citation analysis. All databases were practical in use and offered numerous search facilities. PubMed and Google Scholar are accessed for free. The keyword search with PubMed offers optimal update frequency and includes online early articles; other databases can rate articles by number of citations, as an index of importance. For citation analysis, Scopus offers about 20% more coverage than Web of Science, whereas Google Scholar offers results of inconsistent accuracy. PubMed remains an optimal tool in biomedical electronic research. Scopus covers a wider journal range, of help both in keyword searching and citation analysis, but it is currently limited to recent articles (published after 1995) compared with Web of Science. Google Scholar, as for the Web in general, can help in the retrieval of even the most obscure information but its use is marred by inadequate, less often updated, citation information.

2,696 citations

Journal ArticleDOI
Fei Tao1, Jiangfeng Cheng1, Qinglin Qi1, Meng Zhang1, He Zhang1, Fangyuan Sui1 
TL;DR: In this paper, a new method for product design, manufacturing, and service driven by digital twin is proposed, and three cases are given to illustrate the future applications of digital twin in three phases of a product respectively.
Abstract: Nowadays, along with the application of new-generation information technologies in industry and manufacturing, the big data-driven manufacturing era is coming. However, although various big data in the entire product lifecycle, including product design, manufacturing, and service, can be obtained, it can be found that the current research on product lifecycle data mainly focuses on physical products rather than virtual models. Besides, due to the lack of convergence between product physical and virtual space, the data in product lifecycle is isolated, fragmented, and stagnant, which is useless for manufacturing enterprises. These problems lead to low level of efficiency, intelligence, sustainability in product design, manufacturing, and service phases. However, physical product data, virtual product data, and connected data that tie physical and virtual product are needed to support product design, manufacturing, and service. Therefore, how to generate and use converged cyber-physical data to better serve product lifecycle, so as to drive product design, manufacturing, and service to be more efficient, smart, and sustainable, is emphasized and investigated based on our previous study on big data in product lifecycle management. In this paper, a new method for product design, manufacturing, and service driven by digital twin is proposed. The detailed application methods and frameworks of digital twin-driven product design, manufacturing, and service are investigated. Furthermore, three cases are given to illustrate the future applications of digital twin in the three phases of a product respectively.

1,571 citations

Journal ArticleDOI
TL;DR: This paper thoroughly reviews the state-of-the-art of the DT research concerning the key components of DTs, the current development ofDTs, and the major DT applications in industry and outlines the current challenges and some possible directions for future work.
Abstract: Digital twin (DT) is one of the most promising enabling technologies for realizing smart manufacturing and Industry 4.0. DTs are characterized by the seamless integration between the cyber and physical spaces. The importance of DTs is increasingly recognized by both academia and industry. It has been almost 15 years since the concept of the DT was initially proposed. To date, many DT applications have been successfully implemented in different industries, including product design, production, prognostics and health management, and some other fields. However, at present, no paper has focused on the review of DT applications in industry. In an effort to understand the development and application of DTs in industry, this paper thoroughly reviews the state-of-the-art of the DT research concerning the key components of DTs, the current development of DTs, and the major DT applications in industry. This paper also outlines the current challenges and some possible directions for future work.

1,467 citations

Trending Questions (2)
What are the benefits and losses from digital twin application in construction industry?

The paper does not explicitly mention the benefits and losses of digital twin application in the construction industry.

Literature review of digital entrepreneurship in construction industry?

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