Page 76 - Intro Predictive Maintenance

Benefits of Predictive Maintenance 67

taken belief that lube oil analysis will detect machine problems. If it were the only
technology used, this belief may have some validity; however, other techniques, such
as vibration monitoring, will provide a much more cost-effective means of early detec-
tion. Lube oil analysis is not an effective machinery diagnostic tool. Although some
failure mechanisms will release detectable contaminants, such as bearing Babbitt, into
the lubricant, this analysis technique cannot isolate the root-cause of the problem.

Nothing. Almost 13 percent of those interviewed stated that their predictive mainte-
nance program did not require any change. This response is a little frightening. When
one considers that only 10 percent of the surveyed programs generated a positive con-
tribution to plant performance and more than 50 percent failed to recover the actual
cost of their programs, it is difficult to believe that the programs do not need to be
improved.

This response probably partly results from an indication that too many plant person-
nel do not fully understand predictive maintenance technology. In one of my columns,
I used the example of a program that was judged to be highly successful by plant
personnel, including senior management. After 6 years of a total-plant vibration-
monitoring program, unscheduled delays had been reduced by about 30 percent.
Based exclusively on this statistic, the program was deemed successful, but when eval-
uated from a standpoint of the frequency of scheduled downtime and annual pro-
curement of maintenance spares, another story emerged. Scheduled downtime for
maintenance increased by almost 40 percent and annual cost of replacement parts by
more than 80 percent. As an example, before implementing the predictive maintenance
program, the plant purchased about $4.1 million of bearings each year. In the sixth
year of the program, annual bearing replacement costs exceeded $14 million. Clearly
the program was not successful in all respects.

Don’t Know. Almost 9 percent of those interviewed could not answer this question.
Coupled with the previous response, this can probably be attributed to a lack of viable
program evaluation tools. How do you measure the success of a predictive mainte-
nance program? Is it the number of points monitored? Or the change in the overall
vibration level of monitored machinery? Both of these criteria are too often the only
measurement of a program’s effectiveness.

The true measure of success is capacity. An effective program will result in a positive
increase in first-time-through capacity—this is the only true measure of success. The
converse of the increase in capacity is program cost. This criterion should include all
incremental cost caused by the program, not just the labor required to maintain the
program. For example, the frequency of scheduled or planned repairs may increase as
a result of the program. This increase will generate additional or incremental charges
that must be added to the program cost.

The problem that most programs face is that existing performance tracking programs
do not provide an accurate means of evaluation. Plant data are too often fragmented,
distorted, or conflicting and are not usable as a measurement of program success. This