Expected Failure Time Plot: Difference between revisions
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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. | 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 = | = 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. | Using the cumulative binomial, for a defined sample size, one can compute a rank (Median Rank if at 50% probability) for each ordered failure. | ||
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As an example and for a sample size of 6 the 5%, 50% and 95% ranks would be as follows: | As an example and for a sample size of 6 the 5%, 50% and 95% ranks would be as follows: | ||
<br> | |||
{| border="1" cellspacing="1" cellpadding="1" width="400" align="center" height="400" | |||
{| border="1" cellspacing="1" cellpadding="1" width="400" align="center" | |+ Table 1: 5%, 50% and 95% Ranks for a sample size of 6. | ||
|+ 5%, 50% and 95% Ranks for a sample size of 6. | |||
|- | |- | ||
! scope="col" | Order Number | ! bgcolor="#cccccc" valign="middle" scope="col" align="center" | Order Number | ||
! scope="col" | 5% | ! bgcolor="#cccccc" valign="middle" scope="col" align="center" | 5% | ||
! scope="col" | 50% | ! bgcolor="#cccccc" valign="middle" scope="col" align="center" | 50% | ||
! scope="col" | 95% | ! bgcolor="#cccccc" valign="middle" scope="col" align="center" | 95% | ||
|- | |- | ||
| 1 | | valign="middle" align="center" | 1 | ||
| | | valign="middle" align="center" | 0.85% | ||
| | | valign="middle" align="center" | 10.91% | ||
| | | valign="middle" align="center" | 39.30% | ||
|- | |- | ||
| 2 | | valign="middle" align="center" | 2 | ||
| | | valign="middle" align="center" | 6.29% | ||
| | | valign="middle" align="center" | 26.45% | ||
| | | valign="middle" align="center" | 58.18% | ||
|- | |- | ||
| 3 | | valign="middle" align="center" | 3 | ||
| | | valign="middle" align="center" | 15.32% | ||
| | | valign="middle" align="center" | 42.14% | ||
| | | valign="middle" align="center" | 72.87% | ||
|- | |- | ||
| 4 | | valign="middle" align="center" | 4 | ||
| | | valign="middle" align="center" | 27.13% | ||
| | | valign="middle" align="center" | 57.86% | ||
| | | valign="middle" align="center" | 84.68% | ||
|- | |- | ||
| 5 | | valign="middle" align="center" | 5 | ||
| | | valign="middle" align="center" | 41.82% | ||
| | | valign="middle" align="center" | 73.55% | ||
| | | valign="middle" align="center" | 93.71% | ||
|- | |- | ||
| 6 | | valign="middle" align="center" | 6 | ||
| | | valign="middle" align="center" | 60.70% | ||
| | | valign="middle" align="center" | | ||
| | 89.09% | ||
| valign="middle" align="center" | | |||
99.15% | |||
|} | |} | ||
Furthermore, consider that for the units to be tested the underlying reliability model assumption is given by | |||
<span id="fck_dom_range_temp_1297703273161_340" /> | |||
[[Category:Weibull++]] | |||
[[Category:Test Design]] | |||
[[Category:Special Tools]] | |||
Revision as of 17:04, 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