Page 347 - Intro Predictive Maintenance

338 An Introduction to Predictive Maintenance

Operating Cost

The real cost of implementing and maintaining a predictive maintenance program is
not the initial system cost. Rather, it is the annual labor and overhead costs associated
with acquiring, storing, trending, and analyzing the data required to determine the
operating condition of plant equipment. This is the area where predictive maintenance
systems have the greatest variance in capability. Systems that fully automate data
acquisition, storing, and so on will provide the lowest operating costs. Manual systems
and many of the low-end microprocessor-based systems require substantially more
labor to accomplish the minimum objectives required by predictive maintenance.
The list of users will again help you determine the long-term cost of the various
systems. Most users will share their experience, including a general indication of labor
cost.

The Microprocessor
The data logger or microprocessor selected by your predictive maintenance program
is critical to the program’s success. A wide variety of systems are on the market,
ranging from handheld overall value meters to advanced analyzers that can provide
an almost unlimited amount of data. The key selection parameters for a data acquisi-
tion instrument should include the expertise required to operate, accuracy of data, type
of data, and staffing required to meet the program demands.

Expertise Required to Operate. One of the objectives for using microprocessor-based
predictive maintenance systems is to reduce the expertise required to acquire error-
free, useful vibration and process data from a large population of machinery and
systems within a plant. The system should not require user input to establish maximum
amplitude, measurement bandwidths, filter settings, or allow free-form data input. All
of these functions force the user to be a trained analyst and will increase the cost and
time required to routinely acquire data from plant equipment. Many of the micro-
processors on the market provide easy, menu-driven measurement routes that lead the
user through the process of acquiring accurate data. The ideal system should require
a single key input to automatically acquire, analyze, alarm, and store all pertinent data
from plant equipment. This type of system would enable an unskilled user to quickly
and accurately acquire all of the data required for predictive maintenance.

Accuracy of Data. The microprocessor should be able to automatically acquire accu-
rate, repeatable data from equipment included in the program. The elimination of user
input on filter settings, bandwidths, and other measurement parameters would greatly
improve the accuracy of acquired data. The specific requirements that determine data
accuracy will vary depending on the type of data. For example, a vibration instrument
should be able to average data, reject spurious signals, auto-scale based on measured
energy, and prevent aliasing.

The basis of frequency-domain vibration analysis assumes that we monitor the rota-
tional frequency components of a machine-train. If a single block of data is acquired,