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This article systematically summarises the digital twin technology in the existing scientific field using the bibliometric method, puts forward the critical areas and research directions at different stages of the life cycle of the digital twin research topic. Using R-Studio 'Biblioshiny' to measure scientifically, we visually analyze 514 articles related to digital twin in the Web of Science's core set from 2014 to 2021 (including SCI-Expanded and SSCI database). Firstly, we analyzed the core journals, articles, authors, institutions, relevant countries to determine the vital influence of digital twin-related literature. Secondly, we use theme maps to draw the research topics of digital twin-related literature as icons on the conceptual structure and offer four cluster parts (Motor themes, highly developed and isolated themes, Emerging themes, and Basic themes). Finally, we concluded by summarising the limitations of our study and subsequently highlighted future research directions. The study shows that monitoring, maintenance, and computer vision are research topics with good development momentum. Disturbance observer, reinforcement learning, and friction are relatively small research topics with a good development foundation, and scheduling, process modelling, and deep reinforcement learning are emerging research directions. [ABSTRACT FROM AUTHOR]

Architectural heritage is vulnerable to disasters. Digital technologies can fight destruction and can ensure integrity by monitoring, managing and protecting architectural heritage from disasters. In this paper, we clarify the relationship between disasters, digitalization and architectural heritage conservation for the sustainability of cultural heritage. This study used the PRISMA process, and bibliometric tools VOSviewer and Citespace to explore the potential of digital technologies in the protection of architectural heritage—especially during disaster cycles, from the perspectives of both universal and typicality; the results revealed that digital twins, deep learning, and preventive conservation are currently hot topics in digital preservation research (especially that research which relates to disaster cycles). On this basis, this paper summarizes the relevant technologies involved in architectural heritage preservation from the perspective of the disaster cycle and the digital phase, and proposes three future research directions: accurate prediction of multi-disasters, automatic early warning of structural damages, and intelligent monitoring of human–computer interaction. This paper constructs a new research frame for digital preservation of architectural heritage during disasters, providing theoretical reference and practical guidance for architectural heritage conversation. [ABSTRACT FROM AUTHOR]

Digital twin is the digital representation of an entity, and it drives Industry 4.0. This paper presents a bibliometric analysis of digital twin in the supply chain to help researchers, industry practitioners, and academics to understand the trend, development, and focus of the areas of digital twin in the supply chain. This paper found several key clusters of research, including the designing of a digital twin model, integration of a digital twin model, application of digital twin in quality control, and digital twin in digitalization. In the embryonic stage of research, digital twin was tested in the production line with limited optimization. In the development stage, the importance of digital twin in Industry 4.0 was observed, as big data, machine learning, Industrial Internet of Things, blockchain, edge computing, and cloud-based systems complemented digital twin models. Digital twin was applied to improve sustainability in manufacturing and production logistics. In the current prosperity stage with high annual publications, the recent trends of this topic focus on the integration of deep learning, data models, and artificial intelligence for digitalization. This bibliometric analysis also found that the COVID-19 pandemic drove the start of the prosperity stage of digital twin research in the supply chain. Researchers in this field are slowly moving towards applying digital twin for human-centric systems and mass personalization to prepare to transit to Industry 5.0. [ABSTRACT FROM AUTHOR]

With the advancement of Industry 4.0 and the development of science and technology, industries have seen the advantages of digital twin (DT) implementations and concepts. Although the construction industry is still in the early stage of DT development and implementation, it is urgent for the industry to have a DT agenda. This paper identifies 1158 related bibliographic records from the Web of Science and 745 records from the Derwent Patent Database and quantitatively analyzed them to describe patterns of publications. Two knowledge mapping tools were selected to visualize and analyze the literature in the relevant scientific domain. Then, we integrated clustering, knowledge mapping, and network analysis methods to show the current foci and future directions of DT-MT derived from the data of time distribution, journal areas, and subject distribution. The results indicate that DT is a cross-disciplinary information technology with great development potential, and its development in the construction industry is scattered with the leading advancement in the manufacturing of construction materials and components. The derived knowledge map shows three stages of construction DT, including (1) data collection and creation of DT framework and database; (2) implementation of planning and design modules in detail and control of construction sites; and (3) carrying out asset management and fault prediction in the operation and maintenance phase of projects. The novelty of this paper is the specific analysis of DT in the construction industry. This study adds value to the architecture, engineering, and construction industries by shedding light on the focus of DT practical applications and the formation of a development path of construction DT. • This paper seeks to improve the understanding of Digital Twins in the construction industry. • Helps relevant industries to develop a well-structured development path. • Smart engineering, manufacturing, and construction affect industrial performance and the quality of construction projects. • Integration of clustering, knowledge mapping, and network analysis methods to identify the current foci and future directions. • Prediction of the technology influences and its clean production to enhance domain-general strategy knowledge. [ABSTRACT FROM AUTHOR]