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A Complete Array of Related
Analyses...
Recurrence
Data Analysis
- New in Version 7!
"Life Data Analysis" methods deal with units that experience only one
event, end of life. In contrast, other applications involve repeated
events data where a sample unit may accumulate any number of events over
time. Examples include number of repairs on a product, number and
treatment of recurrent disease episodes, etc. Weibull++ 7
provides both parametric and non-parametric approaches to analyze such
recurrent event data. The non-parametric approach is based on the
well-known Mean Cumulative Function (MCF). The parametric approach is
based on the General Renewal Process (GRP) model, which is particularly
useful in understanding the effects of repairs on system age.
[Click to Enlarge...]
Non-Parametric Life Data Analysis
Weibull++’s Non-Parametric Life Data Analysis module provides
complete support for situations where the analyst does not want to fit a
life model to the data, but instead wants to look at the data non-parametrically.
Techniques include Kaplan-Meier, Simple Actuarial and Standard Actuarial.
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to Enlarge...]
Risk Analysis and Probabilistic Design
- New in Version 7!
You can now use the Monte Carlo simulation tool to perform
relationship-based simulations. The new "User Defined" distribution
feature allows you to specify an equation relating different random
variables. You can then determine the joint pdf for the simulated data
set. This type of simulation has many applications in probabilistic
design, risk analysis, quality control, etc. For example, if the height
and length of a rectangle are distributed, so is the area. To find the
distribution of the area, you can generate random height and length
values based on their corresponding distributions and then apply the
equation A = H x L. A distribution can then be fitted to the resulting
set of area values.
SimuMatic®
- New in Version 7!
With Version 7, Weibull++ integrates the SimuMatic utility, which can be
used to perform a large number of reliability analyses on data sets that
have been created using simulation. You can use this utility to
investigate a variety of reliability questions, including analyses to a)
better understand life data analysis concepts, b) experiment with the
influences of sample sizes and censoring schemes on analysis methods, c)
construct simulation-based confidence bounds, d) better understand the
concepts behind confidence intervals, e) design reliability tests, and
much more!
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to Enlarge...]
Download
the Product
Brochure in *.pdf format (2153
KB)
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Parametric and
Non-Parametric techniques for Recurrence Data Analysis - New in
Version 7!
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Non-Parametric
Life Data Analysis Techniques:
- Kaplan-Meier
- Simple Actuarial
- Standard Actuarial
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Risk Analysis and
Probabilistic Design using Monte Carlo simulation and user-defined
functions
- New in Version 7!
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SimuMatic performs
a large of number of reliability analyses on simulated data sets
- New in Version 7!
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Version 7
