Prognostic Reliability Prediction for Repairable System Based on Non- Parametric Model
Anbar Journal of Engineering Sciences,
2016, Volume 7, Issue 1, Pages 42-49
AbstractEstimation of the reliability for repairable system after maintenance actions is usually
based on mathematical models, which can be classified as parametric and non-parametric
models where the parametric model is required a prior specified life time distribution while
Non-parametric model is that relaxes of the assumption of the life time distribution.
Nonparametric life time models are including proportional hazard model and proportional odd
model. In this paper we develop repairable reliability model concentrate on generalized
repairable model that indicate the mixture of proportional hazard model and proportional odd
model. A proportional hazard-proportional odds (PH-PO) model for the purpose of to
improve the repairable reliability to obtain accurate estimates of reliability for repairable
industrial boiler system at normal operating conditions depending on transformation
parameter for reliability prediction for repairable system that represent Beji industrial boiler
in power plant. The results show the odd model better than hazard model for repairable
system after preventive maintenance depends on time to repair where transformation
parameter (c) equal 0.0525094 it is closer to odds model than hazard model.
In addition, reliability industrial boiler in case without temperature effect is better than
reliability with temperature effect by using exponential model where we note that the
reliability at 500 it is worse state where degrade more than (400,450) .
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