Efficient Plant November 2017 - 56

column | efficiency insight

How to
Justify IoT
Investments
Gary Mintchell
Contributing Editor

Cloud technologies play a significant
role in IIoT solutions. The issue of using
the cloud is over, as it's been proven in
critical IT applications.

| EFFICIENTPLANTMAG.COM

ATELY, EVERYWHERE I
travel, the discussion gets around
to the Internet of Things (IoT)-
sometimes called Industrial Internet of
Things (IIoT). Inevitably, when the term
comes up relative to manufacturing and
production, it's linked to "predictive
analytics." That term is just a broader
application of the more specific term
predictive maintenance (PdM), something this magazine has discussed for
many years.
The Emerson Global Users Exchange
held its annual meeting in Minneapolis
in October. Mike Boudreaux, director of
Emerson's Connected Services business,
led a panel discussion featuring Tom
Madilao of Chevron Oronite (Singapore); Peter Zornio, Emerson Automation Solutions CTO; and representatives
of two supplier partners-Jose Valls of
Microsoft and Dave Van Daralaer of
AT&T.
Madilao discussed using IoT technology to locate people and steam-trap
losses. Tags on plant personnel help
managers and first-responders find
workers in hazardous areas, in case
of an incident. Wireless sensors that
monitor steam traps alert maintenance
technicians to energy-wasting leaks.
Answering a question from someone
in the overflow audience regarding the
difference between "Internet of Things"
and "Industrial Internet of Things,"
Zornio compared it to what GE is
attempting to do with Predix-build
an industrial-business model where the
supplier can sell services based on usage.
A significant part of an IIoT solution is the use of cloud technologies.
Boudreaux commented that the issue of
using the cloud is over. It's been proven
in critical IT applications.

The next question for the panel was
how to financially justify IIoT projects.
Explaining his approach, Chevron's
Madilao suggested picking a small
project: Do the engineering and lay a
baseline, then do a proof of concept
(PoC).
Zornio added, "Target a starter-application area where you have
a predefined benefit. For example,
something that will clearly save energy.
Take a rifle-shot approach rather than a
shotgun one." He further advised avoiding people in analytics and data science
who say "just gather lots and lots of data,
and we'll give you answers to questions
that you didn't even think of." As he
concluded, "Most people want answers
to questions that they have thought of."
Boudreaux followed up with, "Do
what you can easily measure."
In other words, make the PoC project easy to explain and measure. When
you can show the return, you should be
able to get funding for the next level.
If you are attempting an IIoT project
to improve predictive maintenance,
you'll likely find one or more barriers
to adoption. Emerson points to three
major ones: Culture of the company;
lack of a clear strategy, including a clear
business case; and knowledge of which
technologies to use.
By the way, if you have kids, you may
need to advise them on which programming languages they should learn.
Consensus was: JSON, node.js, Python,
R, and bots. EP

Gary Mintchell is an industrialtechnology subject-matter expert.
He can be reached at gmintchell@
efficientplantmag.com.

NOVEMBER 2017

http://www.EFFICIENTPLANTMAG.COM

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