Industrial applications of digital twins

Abstract

A digital twin (DT) is classically defined as the virtual replica of a real-world product, system, being, communities, even cities that are continuously updated with data from its physical counterpart, as well as its environment. It bridges the virtual cyberspace with the physical entities and, as such, is considered to be the pillar of Industry 4.0 and the innovation backbone of the future. A DT is created and used throughout the whole life cycle of the entity it replicates, from cradle to grave, so to speak. This article focuses on the present state of the art of DTs, concentrating on the use of DTs in industry in the context of smart manufacturing, especially from the point of view of plantwide optimization. The main capabilities of DTs (mirroring, shadowing and threading) are discussed in this context. The article concludes with a perspective on the future. This article is part of the theme issue ‘Towards symbiotic autonomous systems’.

Developments of digital twin technologies in industrial, smart city and healthcare sectors: a survey

“…The digital twin technology has recently attracted growing interest among researchers. The definition of digital twin was first proposed by Grieves [14] , which is composed of three components: physical objects, virtual objects, and the links between them. The digital twin structure in [14] is illustrated in Figure 2.…”

“…To disperse the cloud, it can be stated that the three particular pillars of digital twin are digital model, digital shadow, and digital thread [18] . The structure of the digital twin model proposed in [14] .…”

“…Instead, in the early development of the digital twin, most researchers believed that the digital twin usually consisted of only three dimensions: physical, virtual, and connection parts [22,41,42] . Table 1 presents a short summary of how different dimensions of digital twins are understood based on four references [14,[43][44][45] . Moreover, some researchers have the belief that the digital twin is focused on simulation [32,46] , while other researchers argue that digital twins can be stretched from a numerical presentation of physical items to a numerical presentation of the entire organization [47] .…”

“…On the other hand, as the data analysis algorithms, IoT, cloud computing, and AI techniques advance, the combined use of these technologies has enabled the emergence of digital twins that are AI-based virtual replicas of physical systems, as first presented by Grieves [14] . The digital twins (DT) paradigm is nowadays becoming the focus of attention of an increasing number of researchers in various fields, especially in industry [15] , smart cities, and smart health [1,16,17] , which are extremely developed by the rapid development of IoT.…”

Towards symbiotic autonomous systems

“…Furthermore, they analyse the potential for combining data analysis and knowledge-based systems based on this information about production systems and present the results of two feasibility studies. In this context, Jiang et al [7] focus on the present state of the art of DTs, concentrating on the use of DTs in industry in the context of smart manufacturing, especially from the point of view of plantwide optimization. The main capabilities (mirroring, shadowing and threading) and the roles of DTs as enablers of novel functionalities, services and opportunities are discussed.…”