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PREDICTIVE MAINTENANCE
gest customer challenges-or more
accurately, perceived challenges-are
usually their own available resources
and trust, " said Tuttle. " Most customers
feel they don't have the personnel
and the time to support development
of a predictive maintenance program.
There's an assumption it takes multiple
people multiple months or even
years to get a good, reliable program
in place. Customers become daunted
when they realize just how much
equipment and the scale of maintenance
efforts they have at a site. On
the trust side, it's hard to break tradition
and rely on a new system to perform
on 'your' system, no matter how
well it's worked elsewhere. "
Among the other obstacles customers
sometimes bring up is the fear of
false alarms. " Many existing programs
have experienced the situation where an
alarm is always coming up that isn't real
or isn't a concern, and the alarm just gets
shelved or personnel become desensitized, "
Tuttle explained. " Nobody wants
to add to the list of alarms, especially if
that's going to add to the desensitization
problem. It's critical to avoid alarms being
activated just because a threshold is
crossed, but that alarms be verified by
the behavior of the current conditions of
the process, which is something we take
major steps to achieve through customization
and specific element-by-element
deployment of the PdM program. "
Tuttle said Taber's hybridized approach
combined with its personnel's
experience only requires the site
to
retrieve some operating data (1 day),
answer some questions about the different
system processes they want to
focus on (2 to 3 hours), and be available
to answer some follow-up questions.
Taber builds out the PdM program
within its platform, then there's a validation
period where the system provides
notifications and insight while the site
continues its existing program. The site
can monitor and compare the findings
of both approaches for as long as it
takes for the site to be satisfied that it's
seeing favorable results. And then the
switchover can be finalized.
" We also very often work on an incremental
scale, meaning we start with
a small portion of the process or a few
pieces of equipment. Building the PdM
program out on this reduced scale only
takes a few weeks total to be functional,
then we move on to the next piece.
Typically, the reduced scale feels more
manageable to the site, and as these
February 2025 | POWER
perform well, trust is developed in the
system and the remaining steps move
even faster, " Tuttle said.
Consistency Is Essential
At the heart of any successful PdM program
lies a fundamental truth-the quality
of your insights can never exceed the
quality of your input data. Even the most
sophisticated AI algorithms are fundamentally
limited by the data they process.
This is why establishing rigorous
data quality standards and validation processes
isn't just a technical detail, it's the
foundation upon which all reliable PdM
capabilities are built.
" As far as data quality, the key is that
the data is consistently represented.
Even if it's noisy data, if it's a consistent
amount of noise, and it reflects and follows
the process reliably, it can be integrated
within the system, " said Tuttle.
" Similar to our approaches in automation
and controls, we utilize a hybridized
approach to system development, combining
real-world process knowledge
and systems experience with machine
learning and AI, dramatically reducing
the bulk data needs upfront. Doing this,
with just a month or two of process data
representing a 'healthy' component, we
can begin reliably informing predictive
and condition-based maintenance programs, "
added Tuttle.
Implementations Vary
How a system is deployed often changes
based on the scale of installation.
Sites that want only a local deployment
at a specific plant site inside a
firewall can avoid some of the cybersecurity
concerns that others face when
wanting corporate-wide visibility.
For standalone plant sites, the system
is considered a " local, on-prem
installation. " Installed in this arrangement,
the system retrieves real-time
process data from the plant's distributed
control system (DCS) using industry-standard
communication protocols:
either OPC (Open Platform Communications),
which enables secure data exchange
between industrial equipment
from different manufacturers, or Modbus,
one of the oldest and most widely
used industrial protocols for connecting
electronic devices. The system can
then communicate notifications back
to the DCS, displaying them either on a
new monitoring graphic or in the form
of alarms.
" Here the only absolutely required
site changes are to support data communication
setup, " explained Tuttle. " It's
great to have additional sensors and
greater resolution, but we can commonly
do quite a bit with existing signals.
We also commonly build our own HMI
[human-machine interface] available only
within the same network level for more
in-depth information display. "
For corporate-wide visibility, Taber prefers
to avoid the direct DCS link, and rather,
communicates with a historian system
such as PI or something similar. " This way
the established process data pathway for
historical system information retrieval is
used and no other pathway is needed that
involves that critical system, " said Tuttle.
" At this level, more information access
across the organization is obviously supported,
and a suite of HMIs and displays
are generated for various levels of the
organization to interact with. Sometimes
this requires a few additional data points
be added to the existing DCS-to-historian
path, but that's generally the extent of
changes required. "
2. If a PdM program can prevent a turbine from being taken offline for repairs during peak
season, it can literally save tens, if not hundreds, of thousands of dollars for a power company.
Yet, quantifying events that didn't happen is difficult. Source: Envato
www.powermag.com
29

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