Chemical Engineering July 2018 - 18

Newsfront
The Changing Face of
Maintenance
Data analytics, connectivity and machine learning are helping processors maintain facilities in a
more cost-efficient way
IN BRIEF
THE EVOLUTION OF
MAINTENANCE
TODAY'S MAINTENANCE
TOOLBOX
DATA COLLECTION
MOVING DATA
ANALYZING THE DATA
THE BENEFITS
AspenTech
M
odern technologies, such as
smart sensors, data analytics,
the industrial internet of
things (IIoT) and machine
learning, are changing the face of maintenance
to help processors ensure they are
spending their maintenance dollars in the
wisest way possible. While it may seem
like a data-centric maintenance practice
will require a lot of high-tech equipment,
experts say chemical processing facilities
likely have some of the necessary
pieces already in place, and a variety of
approaches allows users to go as light or
as heavy as is desirable (Figure 1).
The evolution of maintenance
" For a long time there was only reactive
maintenance, " says Jerry Browning, senior
advisor for enterprise maintenance, North
America, with IFS (Itasca, Ill.; www.ifsworld.
com). " Something was only fixed when it
broke and maintenance techs ran from fire
to fire. Then came preventive maintenance,
which used available information on life expectancy
of a class of assets to get ahead
of the curve and provide maintenance on a
routine schedule. "
There are pros and cons associated with
FIGURE 1. " The idea of using connectivity and analytics for predictive
maintenance allows users to go all in and look at reliability of
the asset and the business as a system, " says Robert Golightly of
AspenTech. " If you have a system view of what's going on, you can
address the little vulnerabilities, as well as the big upsets, before
they negatively impact the process or the business. "
operation. As a result, the maintenance team
creates a preventive maintenance schedule
that cleans every flowmeter in that unit semiannually
to avoid future shutdowns. While it
may prevent future failure, it could also be
that the shutdown was an anomaly. If that's
the case, maintenance is spending a lot of
time and resources to inspect and clean meters
that are fully functional. "
Not only does this squander time and
preventive maintenance. " The good part is
preventive maintenance can save 10 to 15%
in downtime and repair costs compared to
reactive maintenance. The downside is preventive
maintenance isn't always cost effective
because it is hours- or cycle-driven
and maintenance is performed based upon
tribal knowledge or OEM [original equipment
manufacturer] recommendations on equipment
that may not be in danger of failure. "
Nathan Hedrick, flow product marketing
manager with Endress+Hauser (Greenwood,
Ill.; www.us.endress.com) explains the preventive
maintenance philosophy with the following
example: " A flowmeter may have had
a problem with buildup that shut down the
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money, but it " treats the symptom instead of
the disease, " says Hedrick. " The symptom
would be that the meter caused the process
to shutdown, but the disease could be an
excursion in temperature that caused the
media to solidify and trip up the meter. "
However, had the maintenance team had
access to diagnostics, they may have been
able to address the problem before failure.
Further, if they had access to process data,
they may have been able to see the trend
and identify the root cause of the problem
instead of simply addressing the symptom
at the back end, says Hedrick.
Enter the next evolution of maintenance: predictive
maintenance, which was initially based
upon the actual condition of the equipment itCHEMICAL
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JULY 2018

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Chemical Engineering July 2018

Table of Contents for the Digital Edition of Chemical Engineering July 2018