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This example illustrates how to use the mission profile folio to group failure times based on specified convergence points. This strategy can help you achieve more balanced results from analysis with the Crow Extended model.
Consider a military system that performs three separate tasks:
For each hour of operation, the operational profile states that the system operates in environment E1 70% of the time and in environment E2 30% of the time. In addition, for each hour of operation, the gun must be fired 10 times.
The test data set is shown next.
| Time | Classification | Mode | Time | Classification | Mode | Time | Classification | Mode | ||||
| 0.7 | BC | 17 | 121.9 | BC | 22 | 285 | BD | 13 | ||||
| 3.7 | BC | 17 | 125.5 | BD | 9 | 304 | BD | 9 | ||||
| 13.2 | BC | 17 | 133.4 | BD | 10 | 315.4 | BD | 4 | ||||
| 15 | BD | 1 | 151 | BC | 23 | 317.1 | A | |||||
| 17.6 | BC | 18 | 163 | BC | 24 | 320.6 | A | |||||
| 25.3 | BD | 2 | 164.7 | BD | 9 | 324.5 | BD | 12 | ||||
| 47.5 | BD | 3 | 174.5 | BC | 25 | 324.9 | BD | 10 | ||||
| 54 | BD | 4 | 177.4 | BD | 10 | 342 | BD | 5 | ||||
| 54.5 | BC | 19 | 191.6 | BC | 26 | 350.2 | BD | 3 | ||||
| 56.4 | BD | 5 | 192.7 | BD | 11 | 355.2 | BC | 28 | ||||
| 63.6 | A | 213 | A | 364.6 | BD | 10 | ||||||
| 72.2 | BD | 5 | 244.8 | A | 364.9 | A | ||||||
| 99.2 | BC | 20 | 249 | BD | 12 | 366.3 | BD | 2 | ||||
| 99.6 | BD | 6 | 250.8 | A | 373 | BD | 8 | |||||
| 100.3 | BD | 7 | 260.1 | BD | 1 | 379.4 | BD | 14 | ||||
| 102.5 | A | 263.5 | BD | 8 | 389 | BD | 15 | |||||
| 112 | BD | 8 | 273.1 | A | 394.9 | A | ||||||
| 112.2 | BC | 21 | 274.7 | BD | 6 | 395.2 | BD | 16 | ||||
| 120.9 | BD | 2 | 282.8 | BC | 27 |
In general, it is difficult to manage an operational test so that these operational profiles are continuously met throughout the test. The mission profile folio is used to specify convergence points at which to compare the expected amount of testing and the actual amount of testing to ensure that testing is proceeding according to plan. Having the convergence points also makes it possible to group the data so that the Crow Extended model can be applied directly in such a way that the projection and other key reliability growth parameters can be estimated in a valid fashion. For reliability growth assessments using grouped data, only information between time points in the testing is used.
The convergence points specified in the mission profile are at 100, 250, 320 and 400 hours.
Figure 1: Mission profile folio.
Each profile sheet contains information on expected usage and actual usage at all of these convergence points, as well as at other observation points.
Figure 2: Profile for firing a gun.
Figure 3: Profile for moving under environment E1.
Figure 4: Profile for moving under environment E2.
The following plot shows all 3 profiles, together with their convergence points.
Figure 5: Mission profile plot showing all three profiles and convergence points.
The testing profiles are managed so that the actual operational test profile equals the expected value for the three tasks at each of the convergence points.
The resulting data set is entered in a Failure Times data sheet.
Figure 6: Standard folio with test data.
The mission profile is then used to group the data in a new data sheet within the standard folio by clicking the Mission Profile Analysis icon and choosing the mission profile in the window that appears.
The resulting data sheet contains the grouped version of the original data set, using groups based on the convergence points specified in the mission profile, as shown next.
Figure 7: Standard folio with data grouped according to convergence points.
This allows for a more valid analysis of the test results, since it ensures that the test results are analyzed based on balanced test intervals, where all the mission profiles meet their expected values.
Using the Crow Extended model to analyze the new data sheet yields metrics such as the demonstrated, projected and growth potential MTBF.
Figure 8: Growth potential MTBF plot.
