Chemical Engineering July 2018 - 23

The benefits
In today's competitive process environment,
predictive maintenance should
be used not only to keep the process
up and running, but also to provide
guidance on how to spend maintenance
dollars in the way that provides
the greatest return on investment.
For example, some software provides
advanced simulation, making
it possible to venture beyond just
noting that equipment will fail and
what that means for the process.
" Most simulation will tell you what
will happen if a component fails, "
says Robert Golightly, senior product
marketing manager of the asset
performance business unit with AspenTech
(Bedford, Mass.; www.
aspentech.com). " That's sort of a
'binary' decision process, but we
make it 'analog' with simulation that
looks at the problem on a flow basis
and what happens not only if it fails,
but when it slows down, runs at full
steam or anything in between, which
lets users monetize decisions. "
For example, it's not unusual for
more than one component to require
maintenance at any given time, so
it often becomes a case of determining
which piece of equipment is
more important. " Our software can
prioritize the information by saying,
'Here's six things that are going to go
wrong in the process. These three
don't matter, these three do. Work
on them in this order.' It is the adult
in the room that tells users where to
focus based on economic impact. "
Even further, if users ensure that all
involved costs are considered, including
asset value, maintenance costs,
analytics infrastructure and uptime
of the plant, they can make the right
tradeoffs. " For example, run to failure
with no maintenance also has a place
in the maintenance toolbox, along with
preventive and predictive practices,
but the costs and tradeoffs must be
analyzed for each approach: run to
failure, calendar/hours of operationbased
preventive and predictive, " says
Michael Risse, vice president at Seeq
(Seattle, Wash.; www.seeq.com).
" One customer has created a model
with Seeq where they can see declining
performance in an asset, and trade
off this decrease in asset performance
against the market value of the product
to decide when to perform maintenance.
So rather than optimize for
a process parameter or other metric,
they are making real-time profitability
the priority outcome. "
He continues: " That is where leading
companies are going, not to the
asset or line level, but at the outcome
level of increased ROI [return on investment;
Figure 6]. This can mean
a perfectly good decision is delaying
predictive maintenance that is known
to be required in order to continue
production that will be profitable over
the coming weeks or months. "
SAP's Thalbauer agrees. " The idea
is to build a really intelligent enterprise
that includes connectivity and integration
between all the components, processes
and organizations so that you
may leverage the information in multiple
ways so you can perform actions
as part of the overall business process.
In the end, it's about the intelligent
connection between the equipment
and the business, " he says. n
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JULY 2018
23
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Chemical Engineering July 2018

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