- Let's begin with a simple definition
of a digital twin,
and then we'll dive a little deeper to expand upon it.
A digital twin is a virtual replica
of a physical thing.
This virtual twin exists only as software rendered
by computing power.
For the most part, this definition is reasonably adequate.
But let's explore it further.
Having a digital replica of a physical thing
can significantly improve on one or more
of the following processes,
design, simulation, planning,
building, operating, maintaining,
optimizing, and disposal.
For the design phase,
it's possible to virtually create a solution
and accurately render it operational
before a single physical action is taken.
Then we can simulate that solution
under different types of real scenarios.
For example, isn't it useful to first build
a virtual skyscraper,
then put it through a variety of earthquakes
to accurately understand what might happen?
Based on the data provided,
the design can then be modified.
In the build phase,
a digital twin can be used to provide
the construction specifications
or what we call parametric estimates to different providers.
In this way, a digital twin can be an asset
in streamlining the procurement process.
In addition, and importantly, during build,
sensors are applied to the physical object
in order to collect and transmit data
back to its virtual replica.
This is what enables the magic
during the operational and maintenance phases.
At this point, with enough sensors,
the virtual twin is providing all relevant data
about the state of the physical twin.
For example, an operational machine can render accurately
in its digital twin its temperature, vibration,
speed, and so much more.
All of this becomes possible
because of increasingly better digital technologies
that include faster computers, better telemetry,
that is, the communication of measurements
from a collection point to receiving equipment,
smaller, more accurate sensors, data management,
and artificial intelligence.
During operations, an abundance of data is being collected
and fed back to its digital twin over a digital thread.
Think of this as a data pipeline
that enables analytics of various states and stages.
Backed by artificial intelligence,
the digital twin can identify
and even predict maintenance issues before they happen.
It has become a data-informed model of a physical system.
This compelling feature reduces cost,
since it's typically cheaper
to proactively conduct maintenance
than to repair it after it's broken.
Finally, this continuous real-time feed of data
can help with optimization.
That is, improve its performance by enabling the system
to either automatically modify its own behavior
or by prompting the manual intervention of a human.
Digital twins have become particularly ubiquitous
in the Internet of Things or IoT world.
IoT devices are everywhere now, in our homes,
across our cities, and in our factories,
where we call them industrial IoT devices.
These internet-connected electronics collect
and produce data and services
and interact and communicate with each other
and central systems.
The data collected from these devices
creates detailed knowledge,
enabling capabilities we will discuss in later videos.
The use of digital twins in the context of IoT
will likely be one of the defining qualities
of the future of this topic.
With billions of new IoT devices being deployed
and managed each year,
it must be clear by now that digital twins
have a remarkable future ahead.