# Applications of Digital Twin across Industries: A Review
## 1 Introduction  
The term 'Digital Twin' (DT) has gained popularity recently in academic as well as industrial circles, even though it was conceptualized decades ago. In 2002, [PERSON], who introduced the concept of DT, defined it as \"_A set of virtual information constructs that fully describes a potential or actual physical manufactured product from the micro atomic level to the macro geometrical level. At its optimum, any information that could be obtained from inspecting a physically manufactured product can be obtained from its Digital Twin\"_[1]. When defined as such, a Digital Twin is comprised of three components (Figure 1):  
1. Physical twin: A real-world entity (living/non-living) such as part/product, machine, process, organization, or human, etc. 2. Digital twin: The digital representation of the physical twin with the capability to mimic/mirror its physical counterpart in real time. 3. Linking mechanism: The bidirectional flow of data between the two which operates automatically in real-time. Though DT has been defined by academia and industry in several different ways, one thing that they all agree on is its benefits. It reduces operational costs and time, increases the productivity of the existing system, helps in the decision-making process, improves maintenance schedules and activities, provides remote access, makes a saferworking/operational environment, and promotes sustainability [2]. Owing to the varied advantages and applications of DTs, their adoption in different sectors has accelerated in recent years. As reported by Grand View Research, the global market of DT was estimated at USD 5.04 billion in 2020 and is expected to reach USD 86.09 billion by 2028, with a compound annual growth rate of 42.7% from 2021 to 2028 [3]. One of the reasons the demand for DTs has accelerated is the recent outbreak of the pandemic, COVID-19 [4; 5]. Lockdowns due to the pandemic resulted in supply chain breakage, a shortage of workforce, and remote or non-contact working environment [6], due to which digitization and the advancement of processes with minimum human contact have gained much more importance [4]. According to the Gartner survey, 31% of the companies are using DT for the remote monitoring of assets to reduce the frequency of in-person monitoring, such as hospital patients and mining operations to increase the safety of employees and customers [7]. DT technology has found its applications in different industries going through digital transformation. [PERSON] and [PERSON] [8], in their study on DT applications, identified ten major industrial sectors where DT has been applied. These industries are (i) Aerospace, (ii) Manufacturing, (iii) Healthcare, (iv) Energy, (v) Automotive, (vi) Petroleum, (vii) Public sector, (viii) Mining, (ix) Marine, and (x) Agricultural. They also pointed out that DT in these industries has been used for three main purposes i.e., simulation, monitoring, and control. However, the applications of DT are not just limited to these three purposes only. DT now is used for design, validation, customization, optimization, prediction, and maintenance. According to Juniper Research, the industry which will be leading in DT deployment by 2021 is manufacturing (34%), followed by energy (18%) [9]. This paper provides a summary of the current applications of DT in different industries. To get a better understanding of DT, our previous review paper [2] can be referred to, which talks about the definitions of DT across the literature, its characteristics, types, advantages, and challenges. The DT applications that have been reported in the literature regularly are in the field of manufacturing, cyber-physical systems, or in the context of Industry 4.0 in general [10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23]. There are exceptions, but these review papers either cover only one industry [24; 25; 26; 27; 28; 29; 30; 31; 32; 33; 34] or only a few industries [4; 35; 36; 37; 38].