ReliaSoft > Software > BlockSim 7 > Case Studies > Effect of Inspection Intervals

BlockSim 7 Case Studies

This example studies the effects of different inspection intervals.

Odyssey Air uses inflatable life vests  manufactured by ACME Life Vest Company aboard its commercial aircraft. Odyssey Air wants to study and understand the effect of different inspection intervals.    

• 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 scheduled inspections.

  • Scheduled inspections involve testing all vests on the aircraft. Vests found failed are discarded and replaced with new vests (thus resulting in a mix of vests of different ages aboard an aircraft). 

  • Past replacement data were utilized and a dormant failure distribution for these vests was obtained.  

    • Weibull with Beta = 2.55 and Eta = 6.89 years.

• Odyssey Airlines is contemplating different inspection intervals for these life vests. 

  • Study the effect of  inspections done annually, every two years and every three years.

Problem Setup in BlockSim
One way to approach this in BlockSim is to set up a single block with the given dormant failure distribution. Figure 1 shows the analysis in BlockSim.

• If a vest is found failed it is replaced, thus a corrective action needs to be set for the block.  

  • One can assume instantaneous replacement (zero duration) since the time to do the inspection and replace the vest is not of interest in this analysis.

  • Furthermore and since the vests are replaced with new ones, a restoration factor of 1 can be assumed.

• The corrective action is not initiated until the vest is found failed, thus the corrective action will be based upon an inspection. The "Upon Inspection" setting needs to be utilized. 

  • For annual inspections, the inspection would be once a year and so forth.

Once the problem has been set up, simulation is utilized to see the effect of the inspection intervals. Specifically in this case, what is of interest is the Instantaneous or  Point Availability, A(t). What this gives us (within the context of this problem) is the probability that a vest will be operational (non-failed) at a specific point in time. 

Annual Inspection
Figure 2 shows A(t) when utilizing annual inspections. As it can be seen on the chart, A(t) goes to 1 after each inspection, implying that 100% of the vests are in a non-failed state after the inspection.  

From the plot it can be seen that after 1.5 years, A(t) is approximately 98%, implying that 2% of the vests on the aircraft are in a failed state at that point in time. Furthermore, the following can be noted: 

• The percent non-failed decreases after each inspection.  

• The rate of decrease of A(t) keeps on increasing 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.  

Figures 3 and 4 repeat the analysis using two and three year inspection plans.

Figure 2: A(t) vs. time assuming annual inspection. 
 

Figure 3: A(t) vs. time assuming inspection every two years. 
 

Figure 4: A(t) vs. time assuming inspection every three years. 

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