Evaluation Engineering - 16

SOFTWARE

MODELS AND SIMULATION SUPPORT
DIGITAL TWINS AND INDUSTRIAL IOT
By Rick Nelson, Interim Chief Editor
The concepts of digital transformation and the Industrial IoT are driving
major changes in industry. Yet engineers'
understanding of concepts such as digital
twins is still evolving, according to
Philipp Wallner, industry manager for
industrial automation and machinery at
MathWorks. In an interview with EEEvaluation Engineering, he discussed the
Industrial IoT and cited as examples case
studies involving BuildingIQ, a company
that helps building owners and operators
reduce their energy use, and Transpower,
which transports New Zealand's bulk
electricity from where it is generated to
cities, towns, and some major industrial
users.
EE: What is the state of the Industrial
IoT today?
Philipp Wallner: The
Industrial IoT comes up
in more and more of our
conversations with customers. However, what we
also still see is that only a
few companies have already adopted or
implemented Industrial IoT and have
digital-twin solutions in operation. When
it comes to fully implemented projects,
I would say we're still in the beginning.

Figure 1. Common Industrial IoT topology: MATLAB programs or Simulink models can
be deployed on the edge, asset, or cloud.
Courtesy of MathWorks

assets, edge systems, and to the IT and OT
enterprise systems.
EE: Could you elaborate on digital
twins?
PW: Typically, digital twins are implemented on the edge system or on the OT
system or on both. One trend that we observe in conversations with our customers
is that edge systems really play a more
significant role-mainly for two reasons.
One reason is security. The edge system is
close to the assets. Data doesn't have to
leave the facilities. The second reason is
response time-you get far faster reaction
times with edge systems. Also, bandwidth
limitations are lower if you don't have to
transfer big amounts of raw sensor data
outside of the facilities.

EE: At a high level, what constitutes an
Industrial IoT implementation?

EE: You suggest a reluctance to let data
leave a facility because of security concerns. But isn't the cloud a big part of
the Industrial IoT even though data has
to leave a facility to get to the cloud?

PW: One thing that we see in a typical
Industrial IoT topology is a structure similar to the one that you see in Figure 1. It
includes smart assets connected to other

PW: Yes, another trend in general is that
even though it requires sending data
outside of the facilities, cloud solutions
have become more of a commodity. So,

16

EVALUATION ENGINEERING DECEMBER 2019

once data is preprocessed, we see more
and more customers using cloud solutions, whereas two or three years ago
sending out data through a cloud system
would have been a no-go for most of our
customers.
EE: What are other challenges in successful Industrial IoT implementations?
PW: Another challenge that we see is that
no one organization can provide all the
methods and tools that are required to
make effective use of Industrial IoT systems, and therefore, it is really important
to have an ecosystem in place that covers
different aspects, like handling or implementing real-time algorithms, making
time-sensitive decisions, handling big
amounts of data, and so on. We believe that
this is one aspect that MathWorks handles
quite well. We do have a strong focus to ensure that we don't have a closed system. We
think that a good IoT solution has to come
from different vendors. Therefore, one of
the challenges is really getting the different
vendors and solutions working together.
And that will become even more important
in the next few years when bigger and more
open Industrial IoT implementations find
a way into operation.
Evaluation Engineering

Table of Contents for the Digital Edition of Evaluation Engineering
