Overton, Emerson, Knoxville, Tennessee
hydrocarbon process manufacturing operations are almost unrecognizable from
those of just 10 yr ago. Manufacturers are producing new products to meet new
goals and supply an ever-increasing customer base that seemingly cannot consume
products quickly enough. To meet these expanding needs, plants are relying on
maintenance and reliability teams more than ever before, and those teams are
feeling the strain.
one hand, maintenance and reliability teams have dramatically improved their
abilities and tools over the last few decades. Plant personnel are more effective
than ever with their reliability programs, successfully detecting issues and
performing repairs when aberrations appear. However, most teams would like to
perform those tasks more efficiently than they are. Today’s process
in a tight labor market and under tight cost constraints—have very limited resources. As a result,
teams have been asked to do more with less, which ultimately requires more
solution to this conundrum is built-for-purpose edge analytics devices. Edge
analytics devices use targeted technology to collect vibration and process data
from balance-of plant-assets. The system—at the location of the equipment being monitored—then applies automated,
embedded analytics to alert personnel to common faults for a wide range of
assets, such as fans, motors, gearboxes, pumps and other rotating machinery.
today’s forward-thinking maintenance and reliability teams implement edge
analytics, they are seeing dramatic performance improvements. Personnel are
more productive, asset life is extended, and teams can perform more in-depth,
accurate root cause analysis (RCA) to eliminate failures before they occur.
Improve personnel efficiency. Historically,
plant management could count on a deep bench of experienced technicians to keep
their assets running at peak performance. As these experienced personnel walked
the plant, they used a combination of portable monitoring devices and their own
intuition—based on years
or decades of experience—to
locate, isolate and identify problems with rotating machinery.
the wake of the COVID pandemic, however, many organizations are finding
themselves very short on experienced applicants for available positions. As a
result, many plants are operating with skeleton crews—some organizations are using smaller
groups of centralized experts to support multiple plants across a wide
geographic area. Under these conditions, teams can no longer spend 80% of their
time walking around the plant looking for problems, especially when most of
that time is spent examining assets that may not require attention.
teams must instead focus their efforts so they are spending less time
collecting data and more time working on assets that might present an anomaly. Edge
analytics devices can greatly reduce the amount of time teams spend in the
field by continuously monitoring assets and generating analytics results and
diagnostics right at the source.
that data has been collected and analytics have been generated, the edge device
sends actionable information directly to reliability and maintenance personnel
at their workstations or via a mobile device. Received alerts identify the
issue, the severity and steps for remediation. With everything they need
instantly available, less-experienced personnel can more easily fix problems as
they occur, and highly experienced personnel can spend less time evaluating
problems and more time solving them.
Analytics in action. For one
large process manufacturer, its maintenance and reliability team must monitor more
than 2,000 pumps across multiple business units at its sites. Each site has its
own analyst who is responsible for collecting and analyzing data for applicable
assets (FIG. 1).
recent years, the organization discovered it could not sufficiently staff the analyst
role to stay ahead of mechanical failures occurring in balance-of-plant assets,
so management set a goal to reduce the amount of time analysts spent in the
analytics devices will be critical to accomplishing that goal. Edge devices can
collect data from every unit across the site and automatically notify analysts
of any anomalies. Key personnel will immediately know what assets require
attention and what steps to take, without ever having to go into the field to
collect data. This improved visibility helps the organization operate
successfully with a smaller staff, and will free that staff to focus on other
tasks during times when assets do not need immediate attention.
Extend asset life. Much of the
work in maintaining balance-of-plant equipment is focused around bearings (FIG. 2). Bearings are
subject to many faults—poor
lubrication, misalignment, looseness and more—that are difficult to diagnose before they cause
failure. These difficult-to-diagnose issues are often quick to fix. If teams
could take the isolation, identification and analysis time out of the equation,
they could solve many issues before they evolve into more serious problems.
an under-lubricated bearing. To fix the problem, the technician first must
identify it, which means traveling out to the asset and analyzing it, either
with a portable analyzer, visual inspection, or (more likely) both. If the
asset is far in the field, or even at another site across the country or across
the globe, the time to problem identification is further extended. Under-lubrication
can be difficult to detect, so the time spent at the asset collecting data may
the technician identifies the problem, they must travel back to the shop and
analyze the collected data. Assuming they can correctly identify the problem,
they must then create a work order to have someone go out and lubricate the asset.
The time to repair in this instance is exceedingly long, and it all presumes
the team had enough experienced personnel to perform the regular rounds in the
the same situation, but in this case, the vibration identifying under-lubrication
starts 2 d after the technician performs regularly scheduled rounds on the
asset. It could be days, weeks or months before the asset is examined again,
and all the while wear and tear will be breaking down the bearing. Due to
difficult circumstances like this, many bearings installed in the field fail to
reach their full functional life.
analytics devices deliver a fast return on investment precisely because they
quickly identify critical problems, empowering maintenance and reliability
teams to act before those issues become failures. An edge analytics device
eliminates the time spent examining assets, the inconsistency of inspection by
different personnel, and the time spent analyzing the collected data.
addition, the high performance of the embedded analytics systems enables the
devices to detect and identify issues well before personnel can, giving teams
far more time to intervene before issues become failures. As a result, teams
using edge analytics devices typically find that the realized functional life
of their bearings has been extended.
Improve RCA. One of the
primary benefits of edge analytics devices is that they make it easier for
maintenance and reliability teams to correlate operational data with asset
health data to delve deeper into problems and better identify root causes of
recurring issues. Modern edge analytics devices can bring in different types of
signals: temperature, pressure, analog signals, etc. Armed with this valuable
data as well as traditional vibration data, teams can more easily determine how
external factors may be contributing to the alerts they receive.
the most advanced edge analytics devices can send data to control systems or
receive process data from those systems via Modbus and OPC UA communication to
further identify how process changes impact the health of balance-of-plant
assets. If issues occur due to external factors, this extra layer of analysis
makes it far easier to isolate and remedy any problem.
analytics devices can also be integrated with an organization’s machinery
health software to allow deeper analysis and trending of asset health data. Even
if a plant has analysts working with these systems, the team saves significant
time not just by avoiding sending people to the field to collect data, but also
in providing analysts immediate solutions for the plant’s most common problems,
freeing them to focus their skills on more complex issues.
Analysis in action. At one
process manufacturer that was producing a critical product during the pandemic,
the maintenance and reliability team was delivering data from its edge
analytics devices to its historian to correlate it with operational data. After
detecting high vibration on a fan, but finding no bearing problems, the team
examined the operational data alongside the data from the edge analytics
device. The team determined that the vibration issue occurred because intake
filters on the fan were icing up. The high vibration had nothing to do with a
was external. Once the team removed the ice, operations returned to normal.
Stay ahead of the maintenance curve. Skilled
personnel are central to the operation of a successful maintenance and
reliability team. However, these personnel are often pushed to their limits
simply trying to keep up with maintaining the plant’s assets; analysis and
repairs are often delayed, resulting in high costs, or, in the worst case, production
analytics devices are designed to not only dramatically reduce the low-value
task of walking around the plant collecting data, but also to help teams
develop a routine centered on predictive maintenance. This functionality
empowers them to stay ahead of critical tasks and focus on driving more
efficient operation across a facility, fleet or enterprise. HP
a Emerson’s AMS Asset Monitor
BRIAN OVERTON is the Sales Enablement Manager and subject matter
expert for machinery health products at Emerson. With more than 31 yr with the
organization, Overton’s experience is extensive, covering all aspects of
reliability maintenance. Prior to his tenure with Emerson, he proudly served in
the U.S. Navy as a nuclear-trained electrician, where his foundational
knowledge of reliability maintenance was established. Overton relies on these
years of experience when it comes to product and program development, both internally
and with customers.