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| Tool Tips | |
 What
is the best way to import plots from ReliaSoft applications into Microsoft
applications such as Word or PowerPoint?
The quickest and easiest way is to simply cut and paste. With a plot open, select Copy Plot from the Edit menu to copy the graphic, then paste it into the Word document or PowerPoint presentation. In ALTA and Weibull++, you can also activate the RS Draw tool to annotate the plot and save it as a Windows Metafile (*.wmf). This allows you to share the plot with others who may not have the ReliaSoft application on their computers. In the desired Microsoft application, simply insert the picture into the document (e.g. select Picture then From File from the Insert menu and browse for the *.wmf that you saved).
The reliability and maintainability simulations in BlockSim rely on a random number generator to perform the analyses. Consequently, if you perform consecutive analyses on the same system without specifying a seed for the random number generator, the results will differ each time you run the simulation. If repeatable results are desired, be sure to select the Use Seed option on the Maintainability or Reliability tabs of the Reliability/Maintainability Simulation window and specify the value to be used as the seed.
In
Weibull++, what does the "Use True 3-P MLE on Weibull" option do?
In the Calculations tab of the User Setup in Weibull++, you can select the Use True 3-P MLE on Weibull option to use maximum likelihood estimation (MLE) to determine the parameter estimates for all of the parameters in the three-parameter Weibull distribution.
By default,
this option is not selected and Weibull++ first determines the estimate of
the location parameter,
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by nonlinear regression. Once this estimate is determined, Weibull++ uses
MLE to estimate the other two parameters. It has been found that this
methodology is generally more appropriate for the analysis of life data.
With the Use True 3-P MLE on Weibull option selected, the results
of the analysis may not make sense in the context of life data analysis (e.g.
very large negative values for 
