1-Parameter Weibull Example: Difference between revisions

From ReliaWiki
Jump to navigation Jump to search
m (proofread)
(removed header)
Line 1: Line 1:
<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.  



Revision as of 10:24, 20 July 2012

Weibull Examples Banner.png


New format available! This reference is now available in a new format that offers faster page load, improved display for calculations and images and more targeted search.

As of January 2024, this Reliawiki page will not continue to be updated. Please update all links and bookmarks to the latest references at Weibull examples and Weibull reference examples.





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:
1P Weibull Parameters.png
  • Probability plot:
1P Weibull PPlot.png
  • Use the QCP to predict reliability:
1P Weibull QCP.png

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.