Shades of Digital Twinning
operations with business-value: better ROI,
lower maintenance costs and other
operational benefits. IoT is becoming the
core driver of process improvement. Upper
management may not necessarily care about
the architecture of the IoT, but it does need
to have the right information at the right
time. The architecture is important to ensure
that the maximum benefit from IoT is
realized.
I O T G ROWING P AINS : A D IGITAL
T WIN P ERSPECTIVE
The Internet of Things (IoT) is proliferating
with the advent of affordable and accessible
processors and sensors enabling more
businesses to discover the value in
connecting devices to their Information
Technology (IT) systems. Sensors for devices
are readily available and the cloud has
become ubiquitous. Low-cost data storage
and analysis for processing vast amounts of
data are all merging with new wireless
protocols into a powerful force for digital
industrial transformation.
The focus for IoT and digital twin techniques
has been on data collection, visualization
and comparison with behavioral models: the
twins. These are needed for catching
anomalies that indicate imminent failure,
but they may also show what factors lead to
failure. This information can be used to
mitigate failures by changing system
behavior. This means changing software;
using a device shell on a self-aware system
with version and life-cycle management.
The IoT is ushering in the fourth industrial
age—Industry 4.0—in an evolution of
manufacturing and production from
centralized to decentralized and a merger of
Operational Technology (OT) with IT. The
rise of smart manufacturing is being
propelled by connecting ever more powerful
devices for factory control directly to the
network. As these devices gather and
preprocess operational data, the ability to
mirror machines and their control in digital
models has given rise to the concept of
Digital Twins. Pairing of a digital twin and a
physical device enables virtual analysis and
monitoring to predict and prevent issues
before they impact operations.
An IoT system could be built without
standards. Standards, however, are
necessary to build interoperable IoT
systems. Different aspects of an IoT system
have
different
requirements
for
standardization. Simulation models could
benefit from CAD model standards whereas
device proxies need standard protocols to
talk with the device. Particularly, industrial
systems are often composed of components
from diverse sources. Standards will be
necessary for them to interact.
Defining how IoT devices are developed,
tested, deployed and used across
operations, as well as the interoperability for
updating and improving functions, will
provide individual smart manufacturing
1
Some standards for industrial data exchange
exist, such as OPC-UA 1 ; but they need
updating for security, if nothing else.
https://opcfoundation.org/markets-collaboration/ids/
IIC Journal of Innovation
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