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 a Weibull distribution with | Furthermore, consider that for the units to be tested the underlying reliability model assumption is given by a Weibull distribution with | ||
<math>\beta=2</math>, and <math>\eta=100</math> hr. | |||
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[[Category:Weibull++]] [[Category:Test_Design]] [[Category:Special_Tools]] | [[Category:Weibull++]] [[Category:Test_Design]] [[Category:Special_Tools]] |
Revision as of 17:18, 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 [math]\displaystyle{ \beta=2 }[/math], and [math]\displaystyle{ \eta=100 }[/math] hr.