Page 276 - Improving Machinery Reliability

Maintenance and Benchmarking Reliability 241

Tactical Level Maintenance Measures

Succeeding with strategic level maintenance measurement comparison will gener-
ate significant improvements. Tactical level maintenance measures should be devel-
oped to support the enterprise’s associated tactical goals. Although these measure-
ments are important, no specific measurements are suggested here. These
measurements can be developed in relationship to specific enterprise and mainte-
nance operation situations.

Operational Level Maintenance Measures

The operational level is the lowest level of maintenance measurement. Compar-
isons at this level are not as important as those at the strategic level. Operational
level comparisons are most beneficial in the investigation of specific improvement
situations. Operational level metrics are used primarily by a maintenance department
to better manage its operation. Some suggested operational level metrics folldw:

Total minimum maintenance cost
Life-cycle cost of asset ownership
Mean time between failures
Mean time to restore
Overall equipment effectiveness (a total productive maintenance, or TPM mea-
surement)
Average response time to unscheduled machine failure
Percent of time machine is available to run versus scheduled run time
Periodic customer satisfaction surveys
@ Periodic skilled trades work constraint analysis

These measurements, like the strategic level measurements, must be checked consis-
tently and used to be effective. It is recommended that a maintenance engineering func-
tion be established to manage and use maintenance data, among other responsibilities.

Benchmarking

A benchmarking industry has emerged in recent years, along with a broad range of
measurements (including maintenance measurements) that theoretically define
“world class.” For the most part, these are bottom-line-type measurements that have
value when internal performance is compared. Table 4-2 lists some world-class
value examples for strategic level measurements.*
Various sources contacted for these values indicated that they would not validate
the numbers. There are too many associated variables and there was generally too
much risk associated with publishing the values. Commercial sources felt that their
values were proprietary and that publishing the values divulges information from
which they derive revenue. These are just some of the problems with benchmarking.
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*Numerical values have been adjusted to reflect H. P. BlochlF. K. Geitner’s experience.