Anatomy of CBM
By Murray Wiseman
Extracted from
Chapter 7 of “Reliability-centered Knowledge”
Having understood,
from Figure 6‑4 (page 87), that the decision to perform CBM flows from a
fundamental analysis of the physical asset’s maintenance requirements, we turn
our attention to the composition of a CBM task. We keep the over-riding
concerns in mind. That is, we elect to conduct only applicable and effective
CBM procedures. Figure 7‑1 portrays three distinct CBM sub-processes, each of
which must satisfy the applicability and effectiveness criteria in order for
CBM to add value to a maintenance program.
Figure
7‑1: CBM sub-processes
Data Acquisition
Data acquisition is
the first and, one might assert, the easiest of the three CBM
sub-processes to implement. Assisted by advanced sensor, signal transmission,
and storage technologies, we can, without too much effort, implement systems
that collect and store impressive amounts of data. The predictive maintenance
industry has organized[1]
to provide communication standards and protocols endowing their products with
unprecedented capability to share process and condition monitoring data.
Because commercial-off-the-shelf (COTS) data acquisition hardware and software
products can be used across a range of industries, data acquisition enjoys more
commercial exposure than do the other sub-processes of CBM. Some maintenance
technology consumers imagine that, once they set up elaborate data acquisition,
storage, and display systems, they will have overcome the major hurdle to
effective CBM. Some pay scant attention to the choice of the data they decide
to collect, adopting a when-in-doubt-collect-it-anyway-it-might-be-useful attitude.
Their data choices are influenced largely by the capabilities of the technology
rather than by a pre-assessment of how well the collected data will reflect an
evolving failure mode.
By way of illustration, there are two important reasons why bearings fail :
- Overheating – the most common cause being over-lubrication, and
- Contaminants in the bearing oil – water being the dominant one
Were we to consider
CBM a form of maintenance inspection (rather than a hi-tech maintenance
process), we would demand that monitored data relate clearly to the failure
modes with which we are most concerned. Moreover, from an information
management perspective, we would
require that our CBM and CMMS databases store, in the case of centrifugal
pumps, for example, such “mundane” types of data as:
- Bearing oil reservoir levels and bearing
case temperatures.[2]
- Incidences of leakage from the stuffing
box, gaskets, bearing seals, cracks or holes in the piping or pump
casting.
- Abnormal noise such as that sometimes
heard when air is leaking into a mechanical seal or pipefitting. (Vacuum
leaks can be checked with smoke.)
- Odors indicating high temperature.
- Colors indicating a component has been
subjected to abnormal heat.[3]
- Blackened oil indicating that it has been subjected to high temperatures.
- Excessive vibration detected either with
the use of instruments, or by one of the senses.
- Malfunctioning environmental controls on
stuffing boxes, discernable by measuring the temperature difference
between the inlet and outlet lines.
- Positions of control and isolation valves
throughout the system while the pump is running steadily.
- Flow, differential pressure, power
consumption, temperatures (in the volute and stuffing box), shaft speed,
liquid levels (sight glasses)
- In cartridge seals, estimates of face
loads by measurement of the gap that held the retention clips.
Tradespersons and
operators make these types of observations routinely. Sometimes, they take
approriate corrective action. Seldom, however, do the observation or the
failure mode[4] discovered
as a result of the observation, appear methodically as records in the
maintenance history database. Invaluable sources of reliability data such as these,
elude most maintenance information record keeping processes. Rather, those
historical records contain, mainly, descriptions of activities performed,
without reference to the conditions that inspired the actions. The McNalley
institute[5]
enumerates the possible causes of the elevated temperatures in the stuffing box
as:
- Loss of
circulation in the stuffing box cooling jacket.
- Loss of cooling in the bearing case cooling sump.
- Something is cooling the outside of the bearing casing causing the outside diameter of the bearing to shrink, increasing the load.
- The bearing was installed incorrectly.
- The bearing is over lubricated. The oil level is too high or there is too much grease in the bearing.
- The lubricating oil is contaminated with water.
- The shaft is overloaded because the pump is operating off of the B.E.P. (best efficiency point).
- There is too much axial thrust of the shaft.
- Misallignment, unbalance, etc.
Oil sampling will
indicate the following conditions that are a prelude to (or an indication of) serious
failure.
- Water is getting into the oil.
- Oil additives are no longer present and functioning.
- The oil is carbonizing due to high temperature.
- Solids due to corrosion, bearing-cage destruction, or some other reason are present.
By monitoring pump suction and discharge pressure in concert with product flow and motor amperage, the following failure modes may be detected:
- Wrong size pump.
- Pump operating far from best efficiency point raising the likelihood of shaft deflection.
- Motor close to an overload condition.
- Impeller needs adjustment or the wear rings need replacement.
- Poor operating practices.
- Source product tank at wrong level or suction lines are clogging.
- Getting close to cavitation.
Most failure modes
occur randomly rather than by a wearing out of a component. For example, were
wear the dominant failure mode in bearings, they would, on the average, survive
50 or even 100 years. But, industrial bearings undergo accelerated wear
initiated by randomly occurring internal or environmental events, for example a
shock load, excessive heat, or water ingress causing lubricant failure. Bearing
life is, in addition, highly influenced by initial conditions, for example, how
it was stored and handled prior to installation, and how it was installed.
Randomness, being the
rule, rather than the exception, is it reasonable for us to assume that we will
usually find a monotonically rising trend of some monitored variable throughout
a component’s lifecycle, from which we may predict its failure? A more reasonable
approach to CBM would be to monitor the equipment and its operating context for
signs of conditions causing abnormal stress, that if allowed to persist, will
be destructive. Doctors monitor
cholestrol to determine whether our arteries are in danger of clogging. At a
certain level, they order a corrective action, usually a change in lifestyle.
Maintainers monitor oil levels to avoid the consequences of over- or
under-lubrication. Vibration analysts determine a condition of foundation
weakness, shaft misalignment or of rotor imbalance, that, if uncorrected, will
lead to serious failure.
These examples
illustrate that CBM is a viable maintenance strategy for avoiding failure
altogether. Yet CBM can also track and predict some failure modes from some
point in time after their random initiation to their ultimate functional
failure. It has been estimated[6]
that twenty precent of failure modes proceed in a predictable enough manner
following their detection (their potential failure), that a
repair action may be planned and executed prior to the loss of asset
functionality. A spalled bearing, for example, emits bearing tones that can be
detected automatically through processing of the spectral data assisted by
cepstrum analysis. The bearing may continue to operate adequately from this
point for several months prior to a failure that would render it
non-functional.
It seems, then from
the preceding, that there are two classes of CBM:
a. the detection of abnormal stresses[7]
on a system that, if uncorrected, will provoke a failure that has not yet
initiated, and
b. the detection of a failure that has already
begun, but has not progressed to the point where a required function has been
lost.
In either situation,
CBM is said to be effective, as long as the consequences of failure are reduced
(or avoided entirely) at an acceptable cost.
In the case of the first CBM class, and, pursuing our example of a
centrifugal pump, we might notice a rising trend in the temperature of the
stuffing box. If it gets too hot, we are going to have problem. We had better
correct the condition if we do not want to experience a premature (random) seal
failure. The McNally Institute describes the following seal failure modes that
will be provoked by excessive stuffing box temperatures:
- The product can change its state, insofar as ceasing to act as a lubricant, but partially transforming into a destructive solid.
- The product can vaporize, expand and blow the seal faces open leaving solids between the faces.
- The product can become viscous, interfering with the free movement of the springs and bellows.
- The product can become an adherent, gluing the lapped faces together or making the moveable components inoperable.
- The product can crystallize interfering with the moving parts of the seal.
- Excessive heat can cause the product to build a film on the faces (hot oil as an example) impeding sliding of the components and making them inoperable.
- Corrosion increases with increasing temperatures.
- Thermal expansion may cause seal faces to go out of flat, loosening of pressed-in carbon faces in their holder, and sticking of the bellows’ vibration dampers to the shaft sleave and opening the faces.
- Heat can damage the faces of the plated materials and filled carbon face types.
- Expansion of air pockets in some carbon faces can cause pits in the lapped faces.
- High heat levels can cause elastomers to experience compression set problems, resulting in leakage or in some cases complete failure.
A change in stuffing
box pressures can cause:
- The product to vaporize opening the lapped faces.
- O-rings and other elastomer designs to extrude and jam the sliding components.
- Lapped seal faces to distort and go out of flat.
- A stuffing box vacuum that can blow open unbalanced seals.
- A differential pressure across the elastomer that can cause ethylene oxide to penetrate into the elastomer and destroy it as it expands in the lower pressure side.
When monitoring temperature and pressure in the stuffing box area we will note these changes. Then, by applying our knowledge based rules, we will have adeqate time to react before seal failure occurs. Knowledge based rules form our CBM policy. Without a CBM policy, regardless of the number of sensors scattered throughout our process, the amount of data storage capacity, or the sophistication of the software “shell”, our CBM program will ultimately prove ineffective.