Efficient Plant Nov./Dec. 2022 - 22

department | tech horizons
An ongoing look into the
technologies and trends
that will shape your
manufacturing future
Is it Time T
For a Digital
Twin?
Dr. Klaus M. Blache
Univ. of Tennessee Reliability
and Maintainability Center
(RMC)
HE CONCEPT OF digital
twins has been around for
decades, but it's the connectivity
of everything (supporting the
data flow) that's possible today that
enables it to be more successful. Most
give credit to NASA for modeling/replicating
their spaceships in the 1960s.
Although others applied the concept,
John Vickers coined the term " digital
twin " in 2010.
A digital twin is a physical object and
a digital twin model that passes data
between them (in two directions) with a
synergistic outcome. Once you get to this
capability, you can use it to run scenarios
to get a better/more accurate look into
future possibilities.
According to Gartner, " A digital twin
is a digital representation of a real-world
entity or system. The implementation of
a digital twin is an encapsulated software
object or model that mirrors a unique
physical object, process, organization,
person, or other abstraction. Data from
multiple digital twins can be aggregated
for a composite view across a number of
real-world entities, such as a power plant
or a city, and their related processes. "
(Definition of Digital Twin - IT Glossary
| Gartner)
According to IBM, " A digital twin is
a virtual model designed to accurately
reflect a physical object. The object being
studied, for example, a wind turbine, is
outfitted with various sensors related to
vital areas of functionality. These sensors
produce data about different aspects of
the physical object's performance, such
as energy output, temperature, and
22 | EFFICIENTPLANTMAG.COM
weather conditions. This data is then
relayed to a processing system and
applied to the digital copy. " (What is a
digital twin? | IBM)
A virtual model that is enriched with
good data from sensors and IoT/connectivity
can run scenarios/simulations/
machine learning, with the results going
back into the asset/machine, production
line, entire factory, aircraft, building,
city, and so on. What makes a digital
twin powerful is that it's a continual
back-and-forth of improvement between
real-time plant data going to the digital
twin and system learnings being applied
at the physical asset.
Most of us have seen various simulations
and possibly have performed them.
This is also a virtual model. Digital twins
can run many simulations to analyze a
process. Similar to an FMEA (Failure
Mode and Effects Analysis), you decide
the level (granularity of the effort) or
level of investigation. For example, the
digital twin can be small (for a component)
or large (for an entire production
facility).
Digital twins are most valuable when
projects are complex, large, and require
(and can justify) lots of sensors. This
could be for automobiles (design and
production), aircraft, complex machines,
bridges, locomotive engines, manufacturing/production
with numerous
machines, and power utilities.
In the big picture, use of digital twins
is still in its infancy. My data shows
that in North America (on average),
when looking at digital adoption level
in TPM, remote monitoring is at 48%,
NOV/DEC 2022
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Efficient Plant Nov./Dec. 2022

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