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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. 
  |  | #REDIRECT [[Reliability_Test_Design#Expected_Failure_Times_Plots]]  | 
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 | = Background & Calculations  =
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 | 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: 
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 | <br>
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 | {| border="1" cellspacing="1" cellpadding="1" width="400" align="center"
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 | |+ Table 1: 5%, 50% and 95% Ranks for a sample size of 6.  
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 | |-
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 | ! bgcolor="#cccccc" valign="middle" scope="col" align="center" | Order Number 
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 | ! bgcolor="#cccccc" valign="middle" scope="col" align="center" | 5% 
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 | ! bgcolor="#cccccc" valign="middle" scope="col" align="center" | 50% 
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 | ! bgcolor="#cccccc" valign="middle" scope="col" align="center" | 95%
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 | |-
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 | | valign="middle" align="center" | 1 
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 | | valign="middle" align="center" | 0.85% 
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 | | valign="middle" align="center" | 10.91% 
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 | | valign="middle" align="center" | 39.30%
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 | |-
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 | | valign="middle" align="center" | 2 
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 | | valign="middle" align="center" | 6.29% 
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 | | valign="middle" align="center" | 26.45% 
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 | | valign="middle" align="center" | 58.18%
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 | |-
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 | | valign="middle" align="center" | 3 
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 | | valign="middle" align="center" | 15.32% 
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 | | valign="middle" align="center" | 42.14% 
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 | | valign="middle" align="center" | 72.87%
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 | |-
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 | | valign="middle" align="center" | 4 
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 | | valign="middle" align="center" | 27.13% 
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 | | valign="middle" align="center" | 57.86% 
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 | | valign="middle" align="center" | 84.68%
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 | |-
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 | | valign="middle" align="center" | 5 
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 | | valign="middle" align="center" | 41.82% 
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 | | valign="middle" align="center" | 73.55% 
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 | | valign="middle" align="center" | 93.71%
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 | |-
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 | | valign="middle" align="center" | 6 
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 | | valign="middle" align="center" | 60.70% 
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 | | valign="middle" align="center" | 
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 | 89.09%
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 | | valign="middle" align="center" | 
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 | 99.15%
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 | |}
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 | <br>
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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 <span class="texhtml">β = 2</span>, and <span class="texhtml">η = 100</span> hr. 
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 | Then the median time to failure of the first unit on test can be determined by solving the Weibull reliability equation for t, at each probability, 
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 | or
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 | <math>R(t)=e^{\big({t \over \eta}\big)^\beta}</math> 
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 | then for 0.85%, 
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 | <br><math>1-0.0085=e^{\big({t \over 100}\big)^2}</math> 
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 | and so forths as shown in the table below: 
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 | <br>
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 | <br>
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 | <br>
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 | <br><br>
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 | [[Category:Weibull++]] [[Category:Test_Design]] [[Category:Special_Tools]]  |  |