che_november-2023 - 30

ples of this type of equipment
are non-essential valves, such
as ancillary valves, non-process-central
valves, secondary
support-system valves, and
even certain bypass valving.
Repair is made to these assets
when convenient.
Based on a criticality ranking
FIGURE 1. Whether dealing with brand-new valves, critical
in-service valves, uninstalled spares or decommissioned
valves, it is important to specify the best plan to keep
valves well-maintained
PM routines to maintain the asset in
excellent working condition to meet
the operational requirements. A suitable
intervention may require immediate
action, such as the staging of
supplemental equipment to carry the
lost load or finding alternate means
of meeting service levels.
Medium-criticality asset strategies.
These valve assets can only be
out of service for a short period of
time, otherwise mitigation of resulting
issues might be necessary. While
their performance is important to the
overall facility or process objectives,
their outage will not endanger the
level of service targets in the shortterm.
In this case, sufficient monitoring
is required to plan for the outage
and schedule it accordingly, so that
the outage occurs within an acceptable
timeframe.
Low-criticality asset strategies.
These valve assets can be run to failure
and repaired at will and should
not be on any remote or automated
monitoring program. Typical examfrom
0 to 5 (where 5 is most critical),
Table 1 shows an example of
a typical monitoring and inspection
table that might be used at a
processing facility. Anything with
a criticality ranking over 4 requires
continuous monitoring.
Asset condition
Traditionally, asset condition has been
seen as the single most important
driver of strategies. While condition
plays a part insofar as it influences
short-term risk of failure, it must be
used cautiously, since it is not the only
influence on risk of failure. Much more
broadly, condition drives the specific
need for repair, not necessarily the
strategy or priority, and this is an important
distinction. Broken low-criticality
valves are a lower priority than a
high-criticality valve about to fail.
Failure modes and degradation
A failure mode refers to the ways an
asset can break down or fail. The
ways an asset fails depends on its
components. For maintenance considerations,
an asset is actually just
a collection of failure modes to be
managed. If it is made of electronic
parts, then electronic failures apply. If
it is largely mechanical and dynamic
(rotating, for example) then failures related
to the bearings, shafts and seals
also apply. To illustrate this, consider
a large, motorized flow-control valve
that contains many components.
Tracking one of the essential components
over time, like a bearing, provides
good decision support for an
appropriate lifecycle strategy. Figure
2 illustrates the condition profile of a
bearing over time. The degradation of
a bearing is often marked by an increase
in torque.
In Figure 2, the declining mean time
between failure (MTBF), marked by
the shorter intervals, is as important
as the level of performance achieved
after each refurbishment. A declining
performance after each restoration
and decreasing service interval
together may indicate that the asset
is nearing the end of its useful life. It
may be too expensive to maintain, or
may be falling below minimum in-service
performance requirements. The
stress scoring, a reflection of the operating
context and illustrated by the
light blue line in Figure 2, offers clues
to the decline.
The components that fail (bearings,
in this case) and the rate at which
they fail (days to weeks) greatly influence
the strategy to employ. This is
illustrated in the P-F part of the curve
in Figure 2, and illustrates the point at
which a failure potential is detected
(P), and the point at which the asset or
component has failed (F). See Nowlan
and Heap for their discovery and
discussion on this topic [1]. In conFIGURE
2. This chart shows the condition profile of a bearing over time. The bearing's degradation can be evaluated based on changes in the torque
30
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