Citation: Singh, M.; Srivastava, R.;
Fuenmayor, E.; Kuts, V.; Qiao, Y.;
Murray, N.; Devine, D. Applications
of Digital Twin across Industries: A
Review. Appl. Sci. 2022, 12, 5727.
https://doi.org/10.3390/app12115727
Academic Editor: Arcangelo
Castiglione
Received: 9 May 2022
Accepted: 1 June 2022
Published: 4 June 2022
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Review
Applications of Digital Twin across Industries: A Review
Maulshree Singh
1
, Rupal Srivastava
1,2,†
, Evert Fuenmayor
1,†
, Vladimir Kuts
2,3,4
, Yuansong Qiao
3
,
Niall Murray
3
and Declan Devine
1,
*
1
PRISM Research Institute, Technological University of the Shannon, Midlands Midwest,
Athlone Main Campus, N37 HD68 Athlone, Ireland; m.singh@research.ait.ie (M.S.); rsrivastava@ait.ie (R.S.);
efuenmayor@ait.ie (E.F.)
2
Confirm Smart Manufacturing, Science Foundation Ireland, V94 C928 Limerick, Ireland; vladimir.kuts@ul.ie
3
Software Research Institute, Athlone Institute of Technology, Technological University of the Shannon,
Midlands Midwest, N37 HD68 Athlone, Ireland; yuangsongqiao@ait.ie (Y.Q.); nmurray@ait.ie (N.M.)
4
Department of Electronics and Computer Engineering, University of Limerick, V94 T9PX Limerick, Ireland
* Correspondence: declan.devine@tus.ie; Tel.: +353-90-646-8291
† These authors contributed equally to this work.
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.
Keywords:
Digital Twin; Industry 4.0; Smart Manufacturing; system optimization; predictive maintenance
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, Michael Grieves,
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):
(i)
Physical twin: A real-world entity (living/non-living) such as part/product, machine,
process, organization, or human, etc.
(ii)
Digital twin: The digital representation of the physical twin with the capability to
mimic/mirror its physical counterpart in real time.
(iii)
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 safer
Appl. Sci. 2022, 12, 5727. https://doi.org/10.3390/app12115727 https://www.mdpi.com/journal/applsci
