Example: Parametric RDA - Air Condition Unit

The following table gives the failure times for the air conditioning unit of an aircraft. The observation ended by the time the last failure occurred. [3] $$\begin{matrix} \text{50} & \text{329} & \text{811} & \text{991} & \text{1489} \\ \text{94} & \text{332} & \text{899} & \text{1013} & \text{1512} \\ \text{196} & \text{347} & \text{945} & \text{1152} & \text{1525} \\ \text{268} & \text{544} & \text{950} & \text{1362} & \text{1539} \\ \text{290} & \text{732} & \text{955} & \text{1459} & {} \\ \end{matrix}$$
 * 1. Estimate the GRP model parameters using the Type I virtual age option.


 * 2. Plot the failure number and instantaneous failure intensity vs. time with 90% two-sided confidence bounds.


 * 3. Plot the conditional reliability vs. time with 90% two-sided confidence bounds. The mission start time is 40 and mission time is varying.


 * 4. Using the QCP, calculate the expected failure number and expected instantaneous failure intensity by time 1800.

Solution

Enter the data into a parametric RDA folio in Weibull++. Choose 3 under Parameters and Type I under Settings. Keep the default simulation settings.


 * 1. The estimated parameters are $$\hat{\beta }=1.1976,$$ $$\hat{\lambda }=4.94E-03,$$ $$\hat{q}=0.1344$$.


 * 2. The failure number and instantaneous failure intensity are given in the following plots.






 * 3. The conditional reliability is plotted below.




 * 4. Using QCP, the failure number and instantaneous failure intensity are: