Expected Failure Time Plot: Difference between revisions
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Furthermore, consider that for the units to be tested the underlying reliability model assumption is given by | Furthermore, consider that for the units to be tested the underlying reliability model assumption is given by a Weibull distribution with $\beta=2$ and $\eta=100$ hrs. | ||
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Revision as of 17:16, 14 February 2011
When a reliability life test is planned it is useful to visualize the expected outcome of the experiment. The Expected Failure Time Plot (introduced by ReliaSoft in Weibull++ 8)provides such visual.
Background & Calculations
Using the cumulative binomial, for a defined sample size, one can compute a rank (Median Rank if at 50% probability) for each ordered failure.
As an example and for a sample size of 6 the 5%, 50% and 95% ranks would be as follows:
| Order Number | 5% | 50% | 95% |
|---|---|---|---|
| 1 | 0.85% | 10.91% | 39.30% |
| 2 | 6.29% | 26.45% | 58.18% |
| 3 | 15.32% | 42.14% | 72.87% |
| 4 | 27.13% | 57.86% | 84.68% |
| 5 | 41.82% | 73.55% | 93.71% |
| 6 | 60.70% |
89.09% |
99.15% |
Furthermore, consider that for the units to be tested the underlying reliability model assumption is given by a Weibull distribution with $\beta=2$ and $\eta=100$ hrs.