Efficient Plant April 2020 - 9

feature | digital transformation
MANUFACTURING AND PROCESSING
end users have likely heard quite a bit about how
digital transformation and the industrial internet of
things (IIoT) are key to optimizing their operations.
From a practical standpoint, how does a general term
such as IIoT really qualify as a complete answer for
solving any type of problem? The reality is that digital
transformation is a process that combines manufacturing technology and people to provide visibility to
factory or plant operations as one step toward a connected plant. The result is a foundation that optimizes
operations.
Implementing a connected plant usually involves a
variety of open and vendor-specific communication
protocols to connect assets and then collect and transform raw data into a form that can easily be accessed
and analyzed. Analytics can take multiple forms. For
example, there are well-known mechanisms for analyzing energy consumption and production efficiency.
Advanced analytics can also be used to generate
insights through newly identified correlations across
data sets, helping end users to understand equipment
or process relationships that were not immediately
obvious. Digital transformation is a journey and, as
such, you must walk before you run. By starting at
the right pace, you will gain the knowledge needed to
implement the correct infrastructure.

CONNECTIVITY CHALLENGES

Implementing a connected plant
usually involves a variety of
open and vendor-specific
communication protocols to
connect assets and then collect
and transform raw data into a
form that can easily be accessed
and analyzed. Photo: Jens
Schlueter, Getty Images News

APRIL 2020

EP2004femerson.indd 9

Traditional systems have evolved into hierarchies in
which data flows from one layer to the next. Often, the
truth of the data, its origin, is in the control system.
This data is identified by control variables and used in
logic to operate physical equipment. In addition, this
data and the configuration that drives it may then be
replicated into information technology (IT) and operational technology (OT) systems, and perhaps flow to
a cloud infrastructure, usually for fleet or multi-planlevel analysis.
For most of these applications, accessing the data in
its raw or base state, largely in the form of a tag name
and an associated value, required users to re-create
the information necessary to normalize the data and
understand its production context. This was true for
data consumers such as:
 MES (manufacturing execution systems)
 SCADA (supervisory control and data acquisition)

 historians
 analytics
 remote monitoring
 APM (asset performance management).
However, each of these data consumers often
requires its own tag definitions and asset models so
that data can be arranged into an appropriate context.
While this was a step toward digital transformation,
it introduced difficulties over time as data definitions
diverged. It also required substantial effort to synchronize data sets across applications.
For today's digital-transformation projects, these
challenges are largely overcome by advancements in
processing hardware, software, and communications
technologies. These advancements make it easier and
more practical to get the right edge data into the hands
of people and systems that need it.

CONNECTIVITY
FLATTENS HIERARCHIES
Old production-data hierarchies, often represented as
a Purdue Model, are largely gone. For communications
between various edge-located systems and devices
inside a plant, OPC UA is a well-defined standard that
is growing in importance to become the open protocol
of choice, especially for OT applications.
Because OPC UA is platform agnostic, it works well
on traditional Windows-based applications, as well as
on the growing number of Linux-based IIoT applications. In addition, a new generation of edge
controllers, with virtualized deterministic real-time
and general-purpose operating systems on board,
support OPC UA for data access.
Other fundamental capabilities built into OPC UA
include:
 Information modeling: Allows users to create
data representations of real-world objects so that any
application using the data can be informed of the
context.
 Discovery services: Enable applications to discover compatible sources of data on the network.
 Security: Implements certificate exchanges and
encryption to ensure only authorized applications can
access the proper data managed by the plant OPC UA
servers that may reside in equipment controllers.
It's this set of capabilities that allows OPC UA to
create plug-and-play connectivity in the typically
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Efficient Plant April 2020

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