interval does provide a better optimal solution. This
makes the presumption of this research acceptable.
We also analyze the sensitivity of each parameter
to the optimal solution for the modified PM model
by using the ANOVA method as shown in Table 2.
It can be found that
and c are significantly
sensitive to the optimal total maintenance cost TC.
The results indicate that the optimal TC is
significantly affected by a system’s failure rate (or
aging process) and the unit incremental PM cost of
the restored level of degradation rate.
Table 2: The Sensitivity Analysis for the Optimal Solution
of the New PM Model.
Response: TC
α
=0.05
Source Sum of Square DF Mean Square F Value Prob>F
Model 18730.60 9 2081.18 122.56 < 0.0001
β 16656.19 2 8328.09 490.43 < 0.0001
a 70.26 1 70.26 4.14 0.0450
b 1873.76 3 624.59 36.78 < 0.0001
c 130.39 3 43.46 2.56 0.0603
esidual
1460.39 86 16.98
or Total
20190.99 95
5 CONCLUSIONS
For the PM problem in a finite time span, based on
the fact that a shorter time interval of PM can result
in a better expected total maintenance cost, a
modified degradation-rate-reduction PM model is
developed with no constraint on the PM interval (T).
The algorithm of finding the optimal solution for the
new PM model is also constructed in this paper. It is
shown from the examples that the modified PM
model can provide better optimal solution than the
original PM model. This indicates that the modified
PM model is more suitable for the deteriorating and
repairable systems. For the future work, the
theoretical proof of the existence of the optimal
solution for the modified PM model needs to be
explored.
ACKNOWLEDGEMENTS
This research has been supported by Ministry of
Science and Technology of Taiwan under the project
number MOST101-2221-E-324-011-MY2.
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