Everything you need to know about the digital twin what,how,where is digital twin

1. Digital Twins
MH sharifi
Dec 2023

2. Introduction
• Dr. Michael Grieves:
• The concept of a virtual, digital equivalent to a physical product or
the Digital Twin was introduced in 2003 at my University of Michigan
Executive Course on Product Lifecycle Management (PLM). At the
time this concept was introduced, digital representations of actual
physical products were relatively new and immature.
• Grieves, Michael. (2015). Digital Twin: Manufacturing Excellence through Virtual Factory Replication.

3. Interest trend in Digital Twin as seen through
Google searches

4. Number of articles in the Scopus database whose
abstracts contain the phrase “digital twin” across
the years.

6. Competitors in DIGITAL TWIN
AT&T, Inc.
Andritz AG
ANSYS, Inc.
Altair Engineering, Inc.
Aras Corporation
Asite Ltd.
Arrayworks Software
Akselos SA
51WORLD
ALLPLAN Deutschland GmbH

7. Application of Digital Twin
• Application of DT includes real-time monitoring, designing/planning,
optimization, maintenance, remote access

8. Definitions
• NASA:
• “A Digital Twin is an integrated multiphysics, multiscale, probabilistic simulation of
an as-built vehicle or system that uses the best available physical models, sensor
updates, fleet history, etc., to mirror the life of its corresponding flying twin.”
• Chen :
• “A digital twin is a computerized model of a physical device or system that
represents all functional features and links with the working elements.”
• Liu et al:
• “The digital twin is actually a living model of the physical asset or system, which
continually adapts to operational changes based on the collected online data and
information, and can forecast the future of the corresponding physical counterpart.”

9. BENEFITS OF DIGITAL TWIN
• Improved design
• Improved build
• Better early detection and warnings
• Predictive maintenance
• Aggregated data
• Post-manufacturing visibility of products

10. Similar Concepts
• Similar concepts such as Cyber Physical Systems (CPS) and Internet of
Things (IOT) all focus on the idea of connecting a physical system to
data collection, computational and/or communication systems, but
approaching it from differing perspectives: CPS concept from the
system engineering and control perspective, IOT from a networking
and IT perspective, and Digital Twin from a computational modeling
(machine learning/artificial intelligence) perspective

11. Digital Twin Concept
• Digital Twin concept by stating that it consisted of three components,
a physical product in Real space, a virtual representation of that
product in the Virtual space, and the connections of data and
information that tie the virtual and real products together
Virtual representation :
Idealized representation of
physical reality

12. DIGITAL TWIN MISCONCEPTIONS

13. Digital Model
• A digital model is described as a digital version of a preexisting or planned
physical object, to correctly define a digital model there is to be no automatic
data exchange between the physical model and digital model. Examples of a
digital model could be but not limited to plans for buildings, product designs and
development. The important defining feature is there is no form of automatic
data exchange between the physical system and digital model. This means once
the digital model is created a change made to the physical object has no impact
on the digital model either way.

14. Digital Shadow
• A digital shadow is a digital representation of an object that has a
one-way flow between the physical and digital object. A change in
the state of the physical object leads to a change in the digital object
and not vice versus.
• Web tracking isn’t always bad — personal data can make your browsing
more personalised, and provide advertising revenue for sites you like. But
it’s your right to know what data is being collected about you. (Mark Surman)

15. Digital Twin
• If the data flows between an existing physical object and a digital object, and
they are fully integrated in both directions, this constituted the reference “Digital
Twin”. A change made to the physical object automatically leads to a change in
the digital object and vice versa.
• Amongst the misconceptions is the misconception Digital Twins have to be an exact 3D model of a physical thing. On
the other hand, some individuals that think a Digital Twin is just a 3D model.

16. Digital Model Vs Digital Shadow Vs Digital Twin

17. • Distinguishing a Digital Twin from other digital modeling and simulation approaches is based on
the following qualifiers:
• 1. The virtual representation represents a single instance of a physical system; and
• 2. Data/information from the physical system is used to update the states of the virtual
representation over time.

18. DIGITAL TWIN APPLICATIONS

19. Smart Cities

20. Manufacturing

23. Manufacturing (CONT)
• The Digital Twin has the potential to give real-time status on machines
performance as well as production line feedback. It gives the manufacturer the
ability to predict issues sooner. Digital Twin use increases connectivity and
feedback between devices, in turn, improving reliability and performance. AI
algorithms coupled Digital Twins have the potential for greater accuracy as the
machine can hold large amounts of data, needed for performance and prediction
analysis. The Digital Twin is creating an environment to test products as well as a
system that acts on real-time data, within a manufacturing setting this has the
potential to be a hugely valuable asset.

24. Healthcare
• The increased connectivity is only growing the potential application
of Digital Twin use within the healthcare sector. One future
application is a Digital Twin of a human, giving a real-time analysis of
the body. A more realistic current application is a Digital Twin used
for simulating the effects of certain drugs. Another application sees
the use of a Digital Twin for planning and performing surgical
procedures.
• https://www.youtube.com/watch?v=C_0UOdv2d2A
• https://www.youtube.com/watch?v=lGA_Lto9UfI

25. CHALLENGES
• It is becoming more evident that Digital Twin runs in parallel with AI
and IoT technology resulting in shared challenges

26. DATA ANALYTIC CHALLENGES
• IT Infrastructure
• Data
• Privacy and Security
• Trust

27. IOT/IIOT CHALLENGES
• Data, Privacy, Security and Trust
• Infrastructure
• Connectivity

28. DIGITAL TWIN CHALLENGES
• IT Infrastructure
• Useful Data
• Privacy and Security
• Trust
• Expectations
• Standardised Modelling

29. ENABLING TECHNOLOGIES

30. ENABLING TECHNOLOGIES

32. OPEN RESEARCH
• DIGITAL TWIN IN MANUFACTURING
• DIGITAL TWIN IN HEALTHCARE
• DIGITAL TWIN IN SMART CITIES

33. CHALLENGES TO OPEN RESEARCH
• Multidisciplinarity
• Standardisation
• many new and emerging technologies, another challenge facing Digital Twin is with the lack of
standardisation. This results in discrepancies between projects in Digital Twin. A contributing
factor is the variety of definitions seen; this, coupled with no standardisation is a challenge,
slowing the progress of the Digital Twin technology
• Global Advancements
• Futuristic and unrealistic goals lead to slower uptake and development of newly adapted
technologies and opinions. With the breakthrough of Industry 4.0 and the rapid growth of
digitalisation comes the growth of technologies at different rates. However, the accelerated
growth leads to a range of challenges with connectivity and data exchange. For example, the
supporting systems or IoT devices may not be compatible with the Digital Twin. This growth at
different rates can also pose new challenges for security in terms of exposing vulnerabilities

34. Example Digital Twin models

38. INTEGRATING ML INTO DIGITAL TWIN

39. Research topics related to digital twins
Dynamic Data Integration in Digital Twins
Enhancing Cybersecurity for Digital Twins
Human-in-the-Loop Interaction in Digital Twins
Digital Twins in Healthcare Applications
Sustainability Optimization with Digital Twins
Fault Detection and Predictive Maintenance in Digital Twins
Ethical Considerations in Digital Twin Development
Digital Twins for Smart Cities Planning
Interoperability Standards for Digital Twins
Blockchain Integration with Digital Twins

40. Doctoral project: Digital twin developments
within Volvo CE
https://lnu.se/en/research/research-projects/doctoral-project-digital-
twin-developments-within-volvo-ce/