Meng Zhang, F. Tao, Biqing Huang, Ang Liu, Lihui Wang, N. Anwer, A. Nee
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引用次数: 23
Abstract
As a promising technology to converge the traditional industry with the digital economy, digital twin (DT) is being investigated by researchers and practitioners across many different fields. The importance of data to DT cannot be overstated. Data plays critical roles in constructing virtual models, building cyber-physical connections, and executing intelligent operations. The unique characteristics of DT put forward a set of new requirements on data. Against this background, this paper discusses the emerging requirements on DT-related data with respect to data gathering, mining, fusion, interaction, iterative optimization, universality, and on-demand usage. A new notion, namely digital twin data (DTD), is introduced. This paper explores some basic principles and methods for DTD gathering, storage, interaction, association, fusion, evolution and servitization, as well as the key enabling technologies. Based on the theoretical underpinning provided in this paper, it is expected that more DT researchers and practitioners can incorporate DTD into their DT development process.
期刊介绍:
Digital Twin is a rapid multidisciplinary open access publishing platform for state-of-the-art, basic, scientific and applied research on digital twin technologies. Digital Twin covers all areas related digital twin technologies, including broad fields such as smart manufacturing, civil and industrial engineering, healthcare, agriculture, and many others. The platform is open to submissions from researchers, practitioners and experts, and all articles will benefit from open peer review.
The aim of Digital Twin is to advance the state-of-the-art in digital twin research and encourage innovation by highlighting efficient, robust and sustainable multidisciplinary applications across a variety of fields. Challenges can be addressed using theoretical, methodological, and technological approaches.
The scope of Digital Twin includes, but is not limited to, the following areas:
● Digital twin concepts, architecture, and frameworks
● Digital twin theory and method
● Digital twin key technologies and tools
● Digital twin applications and case studies
● Digital twin implementation
● Digital twin services
● Digital twin security
● Digital twin standards
Digital twin also focuses on applications within and across broad sectors including:
● Smart manufacturing
● Aviation and aerospace
● Smart cities and construction
● Healthcare and medicine
● Robotics
● Shipping, vehicles and railways
● Industrial engineering and engineering management
● Agriculture
● Mining
● Power, energy and environment
Digital Twin features a range of article types including research articles, case studies, method articles, study protocols, software tools, systematic reviews, data notes, brief reports, and opinion articles.