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| Case Study 3: Developmental Testing with Corrective Actions Implemented During the Test and Delayed Fixes |
Software
Used: |
| This case study is based on the paper An Extended Reliability Growth Model For Managing And Accessing Corrective Actions by Dr. Larry Crow, presented at the 2004 RAMS. [Click here to download the paper (*.pdf, 238 KB)] |
A product undergoes 400 hours of developmental testing. During testing, the observed failure modes are identified and:
The data set is given next:
Failure Time |
Failure |
|
Failure Time |
Failure |
|
0.7 |
BC1 |
|
192.7 |
BD11 |
|
3.7 |
BC1 |
|
213 |
A |
|
13.2 |
BC1 |
|
244.8 |
A |
|
15 |
BD1 |
|
249 |
BD12 |
|
17.6 |
BC2 |
|
250.8 |
A |
|
25.3 |
BD2 |
|
260.1 |
BD1 |
|
47.5 |
BD3 |
|
263.5 |
BD8 |
|
54 |
BD4 |
|
273.1 |
A |
|
54.5 |
BC3 |
|
274.7 |
BD6 |
|
56.4 |
BD5 |
|
282.8 |
BC11 |
|
63.6 |
A |
|
285 |
BD13 |
|
72.2 |
BD5 |
|
304 |
BD9 |
|
99.2 |
BC4 |
|
315.4 |
BD4 |
|
99.6 |
BD6 |
|
317.1 |
A |
|
100.3 |
BD7 |
|
320.6 |
A |
|
102.5 |
A |
|
324.5 |
BD12 |
|
112 |
BD8 |
|
324.9 |
BD10 |
|
112.2 |
BC5 |
|
342 |
BD5 |
|
120.9 |
BD2 |
|
350.2 |
BD3 |
|
121.9 |
BC6 |
|
355.2 |
BC12 |
|
125.5 |
BD9 |
|
364.6 |
BD10 |
|
133.4 |
BD10 |
|
364.9 |
A |
|
151 |
BC7 |
|
366.3 |
BD2 |
|
163 |
BC8 |
|
373 |
BD8 |
|
164.7 |
BD9 |
|
379.4 |
BD14 |
|
174.5 |
BC9 |
|
389 |
BD15 |
|
177.4 |
BD10 |
|
394.9 |
A |
|
191.6 |
BC10 |
|
395.2 |
BD16 |
Furthermore, an effectiveness factor based on engineering assessment has been assigned for the BD failure modes (delayed fixes). This is given in the following table. The effectiveness factor is the expected fractional decrease in failure intensity of a failure mode after the implementation of a corrective action.
|
BD |
Effectiveness |
|
1 |
.7 |
|
2 |
.7 |
|
3 |
.8 |
|
4 |
.8 |
|
5 |
.9 |
|
6 |
.9 |
|
7 |
.5 |
|
8 |
.9 |
|
9 |
.9 |
|
10 |
.7 |
|
11 |
.7 |
|
12 |
.6 |
|
13 |
.6 |
|
14 |
.7 |
|
15 |
.7 |
|
16 |
.5 |
Data Entry
A new Data Entry Spreadsheet
is created using the Data Type Expert by selecting the following
option.

Once the Data Entry Spreadsheet has been created, the model is changed to Crow Extended and the data are entered. An effectiveness factor is then assigned to each BD failure mode, as shown next. (Note that when using the Crow Extended model, it is common practice to calculate the unbiased beta. You can specify to calculate the unbiased beta via the User Setup.)
Finally, the time at which the test terminates is specified:

Results and Discussion
The achieved MTBF for this system is 7.85
hr, which is the result of the corrective action taken during the test
(BC modes). If the 16 delayed corrective actions are implemented
(BD modes), the MTBF is projected to be 11.32 hr.
If testing continues with the current management strategy in place
(i.e. modes corrected vs. modes not corrected) and with the current
effectiveness of each corrective action, then the maximum attainable MTBF
is 15.00 hr. This is called the Growth Potential MTBF. The
following plot illustrates these results.

The management strategy can be summarized in the Failure Mode Strategy plot.

This plot breaks down the failure
intensity into contributing factors. It shows that 9.48%
have been left in the system (A modes), while 13.4% were removed during
testing (BC - Seen modes). From the analysis, an estimated 31.81% of the
failure intensity were not observed during testing, but would have been
corrected if they had been observed (BC - Unseen modes). In addition,
8.76% will be removed after the delayed corrective
actions are implemented (BD - Removed modes) and 33.23% have not yet
been observed but will be removed by the delayed corrective actions (BD
- Unseen modes), while 3.32% will remain (BD - Remain modes).
The MTBF of each individual failure mode can be plotted and the failure
modes with the lowest MTBF can be identified. These are the failure
modes that cause the majority of the system failures. This is
illustrated in the next plot.

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