The basic application of predictive
maintenance involves taking measurements and applying the technology
or processes to predict failures. The approach should include the
assessment of the equipment as it relates to the business or
personnel safety, prioritizing the equipment, and targeting the
critical equipment.
For predictive maintenance, one other
criterion must be utilized in the assessment process: the monetary
value of the equipment. Even if the equipment is not critical, its
value may warrant the use of predictive maintenance to reduce
potential catastrophic failure of expensive equipment.
It is important to target this most
critical and valuable equipment for predictive maintenance because
there is an associated cost to predictive maintenance implementation.
Predictive maintenance technologies are valuable tools if applied
appropriately. These include the following:
● Vibration analysis
● Motor circuit analysis
● Infrared imaging
● Ultrasound
● Oil analysis
● Ferrography (wear-particle oil
analysis)
These technologies, when applied
properly, can reduce catastrophic failure, and thus maintenance cost.
One other application is statistical process control (SPC). This
predictive tool can be used to predict failures, but a plan must be
in place first, for the data collection process is critical.
If a CMMS is used, then the proper
system architecture must be developed, along with associated
processes and procedures that allow for accurate data collection.
Mean time between failures (MTBF) is determined using the
technologies and processes listed previously.
This will allow for proper planning of
preventive maintenance based on information, not just on recommended
schedules. Using these technologies and SPC should reduce the cost of
equipment maintenance over time. One of the key approaches to a good
predictive maintenance program is consistency or standardization.
For example, if data on equipment
failures (problem, cause, and remedy) do not include a list of
standards, utilizing SPC becomes difficult and will require extensive
research to identify what the data really mean. The cost savings will
be lost because of the hours expended researching this information.
Developing a strategy and approach is
the key to program success. Predictive Maintenance Cost Savings and
Avoidance Potential. Utilizing predictive maintenance can reduce the
overall cost of facilities operation. In a facility where rotating
equipment is prevalent, applying vibration analysis, ferrography, and
laser alignment to coupled equipment may reduce power consumption.
This is assuming that the coupled
equipment is out of alignment, or has undetected wear condition.
Utilizing thermographic imaging will reduce power loss by detecting
loose connections and following up with corrective action.
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