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BlockSim Example 3 – Effect of Inspection Intervals

Download Example File for Version 10 (*.rsgz10) or Version 9 (*.rsr9)

This example studies the effects of different inspection intervals on a system’s point availability.

Example

Odyssey Airlines uses inflatable life vests manufactured by ACME Life Vest Company aboard its commercial aircraft. All the vests on the aircraft undergo scheduled inspections. The vests are stored until they are required for use; therefore, failures remain dormant until the system is needed, or failed vests are discovered during inspections. Vests found failed are discarded and replaced with new vests (thus resulting in a mix of vests of different ages aboard an aircraft).

According to the replacement data obtained from past inspections, the dormant failure distribution for these vests follows a Weibull distribution with beta = 2.55 and eta = 6.89 years.

Odyssey Airlines is considering different inspection intervals for these life vests. The objective is to study the effect of inspections done annually, every two years and every three years.

Analysis

One way to approach this in BlockSim is to use a simulation diagram and set up a single block with a universal reliability definition (URD) that describes the dormant failure distribution. The following figure shows the Block Properties window for the block representing the life vest. The steps for configuring the URD are described next.

Figure 1: Block Properties Window for the Life Vest

Step 1: To define the reliability of the vest, double-click the Model-Reliability field in the Universal Reliability Definition area (shown in Figure 1). This opens the Model Wizard, which allows you to define the failure distribution of the block, as shown next.

Figure 2: Model Wizard

Step 2: During inspection, if a vest is found failed, it is replaced; thus a corrective task needs to be set for the block. To do this, double-click the Corrective Task field in the Universal Reliability Definition area (shown in Figure 1). This opens a Maintenance Task window that allows you to enter the details of the corrective task.

The corrective task is set to start when the the item is found failed during an inspection, as shown next. In this case, we assume an instantaneous replacement (zero task duration) because the time to do the inspection and replace the vest is not of interest in this analysis; therefore, the Task Duration field is left at its default setting (immediate repair). In addition, because failed vests are replaced with new ones, the task restores the vests to an as good as new condition.

Figure 3: Maintenance Task Window for a Corrective Task

Step 3: The corrective action that was set in Step 2 is not initiated until the vest is inspected and found failed; therefore, the inspection task needs to be defined. To do this, double-click the Scheduled Task field in the Universal Reliability Definition area (shown in Figure 1). This opens a Maintenance Task window that allows you to enter the details of the inspection. The following example shows the settings for the annual inspection. The 2- and 3-year inspection tasks can be set up in a similar manner.

Figure 4: Maintenance Task Window for a Scheduled Task

Step 4: Once the properties of the block are set up, use simulation to see the effect of the inspection interval. In this case, the metric of interest is the Instantaneous or Point Availability A(t), which calculates (within the context of this example) the probability that a vest will be operational (non-failed) at a specific point in time. The following picture shows the Maintainability/Availability Simulation window in BlockSim.

Figure 5: Maintainability/Availability Simulation Window

To run a simulation for the 2- or 3-year inspections, you will need to configure the URD of the life vest to use the corresponding inspection interval. You can add or edit the inspection task by clicking the Inspection Task field in the Universal Reliability Definition area (shown in Figure 1).

Point Availability Plots

The following plot shows the analysis with the annual inspections for a period of 15 years. The x-axis shows the time period while the y-axis shows the estimated A(t). As you can see, A(t) approaches a value close to 1 after each inspection, implying that 100% of the vests are in a non-failed state after each inspection.

Figure 6: Point Availability Plot – Annual Inspection

On the 3rd year, the value of A(t) is approximately 95%. This implies that 5% of the vests on the aircraft are in a failed state at that point in time. Furthermore, note the following:

• The percent non-failed decreases after each inspection.
• The rate of decrease of A(t) increases after each subsequent inspection (since non-failed vests are not replaced and the population ages) until a periodic reversal point is reached at which most vests are replaced with newer ones, thus yielding a younger population.

The following plots show the analysis using the 2- and 3-year inspection plans for the same period of 15 years. As you can see, the longer the inspection interval, the higher the rate of decrease of A(t) after each subsequent inspection.

Figure 7: Point Availability Plot – Two Year Inspection Plan