1-Parameter Weibull Example: Difference between revisions
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<noinclude>{{Banner Weibull Examples}}</noinclude> | <noinclude>{{Banner Weibull Examples}}</noinclude> | ||
'''Weibull++ Standard Folio Data 1P-Weibull''' | '''Weibull++ Standard Folio Data 1P-Weibull''' | ||
Six prototypes of a system were tested. The failure times are 16, 34, 53, 75, 93 and 120. Due to the small sample size, the 1P-Weibull distribution is chosen to model the data. According to previous similar products, the slope parameter <math>\beta </math> is 1.5. | Six prototypes of a system were tested. The failure times are 16, 34, 53, 75, 93 and 120. Due to the small sample size, the 1P-Weibull distribution is chosen to model the data. According to previous similar products, the slope parameter <math>\beta </math> is 1.5. | ||
'''Solution''' | '''Solution''' | ||
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[[Image:1P Weibull Parameters.png|center]] | [[Image:1P Weibull Parameters.png|center]] | ||
* Probability plot: | * Probability plot: | ||
[[Image:1P Weibull PPlot.png|center| | [[Image:1P Weibull PPlot.png|center|500px]] | ||
* Use the QCP to predict reliability: | * Use the QCP to predict reliability: | ||
[[Image:1P Weibull QCP.png|center| | [[Image:1P Weibull QCP.png|center|500px]] | ||
The QCP shows that the reliability at 15 hours is 0.9054, and its two-sided confidence bounds at a confidence level of 90% are 0.7619 and 0.9644. | The QCP shows that the reliability at 15 hours is 0.9054, and its two-sided confidence bounds at a confidence level of 90% are 0.7619 and 0.9644. | ||
Latest revision as of 03:24, 8 August 2012
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Weibull++ Standard Folio Data 1P-Weibull
Six prototypes of a system were tested. The failure times are 16, 34, 53, 75, 93 and 120. Due to the small sample size, the 1P-Weibull distribution is chosen to model the data. According to previous similar products, the slope parameter [math]\displaystyle{ \beta }[/math] is 1.5.
Solution
Choose the 1P-Weibull distribution in Weibull++ and calculate it, the results are given below.
- Estimated model parameters:
- Probability plot:
- Use the QCP to predict reliability:
The QCP shows that the reliability at 15 hours is 0.9054, and its two-sided confidence bounds at a confidence level of 90% are 0.7619 and 0.9644.