Expected Failure Time Plot: Difference between revisions

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<math>\beta=2</math>,  and <math>\eta=100</math> hr.  
<math>\beta=2</math>,  and <math>\eta=100</math> hr.  


Then the median time to failure of the first unit on test can be determined by





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:


Table 1: 5%, 50% and 95% Ranks for a sample size of 6. 
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.

Then the median time to failure of the first unit on test can be determined by