MACHINERY LUBRICATION- INDIA MARCH-APRIL 2020 | Page 11

MLI
Figure 2. Readings from an oil-quality sensor used to monitor oil changes on a piece
of mining equipment
Event Detection
Although these sensors cannot replace
laboratory analysis results, they can provide
the necessary insight to make preventive
maintenance decisions before damage
occurs. New sensor technologies utilize
electrochemical impedance spectroscopy
(EIS), which covers a broad spectrum of oil
properties and enables sensitivity to most
failure modes.
In Figure 1, an online oil-quality sensor
was installed on a diesel engine operating
in off-highway conditions. After an oil
change, there was a break-in period, and
the oil-quality reading peaked for that
cycle. As the engine continued in operation,
the sensor readings trended down as the oil
quality degraded.
While in operation, the engine developed
a coolant leak that would have gone
undetected and severely damaged the
equipment, forcing a full engine rebuild.
Upon a significant break in the oil-quality
trendline and an increase in relative
humidity detected by the sensor, an
investigation discovered the coolant leak.
The equipment was repaired, and the oil
was changed and put back into service with
minimal downtime.
Oil Drain Optimization
Optimizing oil drains is another important
benefit of oil-quality monitoring. Unlike
previous generations, the newest sensors
can track and trend most of the major
indicators for condemning the oil. Figure
1 offers a good example of a normal
trendline: The oil has a break-in period,
peaks and then degrades over time. This
degradation of the trendline lets you predict
when condemning limits will be crossed,
allowing the oil’s remaining useful life to
be forecasted. Being able to not only detect
when oil changes are required but also to
predict the oil’s lifespan is a major enabler
for oil drain optimization.
In Figure 2, an operator installed an
oil-quality sensor on a piece of mining
equipment to monitor oil changes. Upon
review, it was found that the oil changes
were occurring on average at around 25
percent of the total remaining useful life.
This left approximately 75 percent of the
oil’s life unused. In most cases, the oil was
changed before it had even been broken in.
By using the data provided by the online
sensor, the operator was able to change the
drain interval practices from being based
on the number of in-service hours to being
condition-based. This has led to a big
savings per asset per year through decreased
oil consumption while significantly
reducing downtime and environmental
waste in the process.
Additional Improvements
New sensing technology is just now
starting to reveal all the ways that it can
help reliability programs. As the use of
these sensors increases, more improvements
can be expected, from optimizing top-offs
and bleed-and-feed methods to advanced
filtration, additive replenishment systems,
etc. For now, these early wins are driving
adoption at a significant rate by changing
the way best-in-class reliability programs
operate. ML
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