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The latest upgrade to
Weibull++, Version 7, provides many
new and enhanced features. This page presents a summary of these features.
Enhanced
Interface with Project Explorer
In Version 7, the Weibull++
interface has been enhanced to allow you to manage multiple analysis
folios and related information all together in a single file. Using the
intuitive "Project Explorer" approach that was first introduced in ReliaSoft's
BlockSim software, Weibull++ now
provides an intuitive, hierarchical (tree) view to allow you to view and
manage one or many standard folios, specialized folios, plot sheets,
reliability block diagrams, spreadsheet reports and/or attached documents
per project. At the same time, the new work environment "stays true to
its roots" so that users who are familiar with previous versions of the
software will be able to enter and analyze data in much the same way as
always.
Weibull++ 7 interface with multiple
data folios, specialized analyses, plots, diagrams, attachments, etc.
all together in the same project file. [Click
to Enlarge...]
Reliability Block
Diagrams (RBDs) for Failure Mode Analysis
The Competing Failure Modes option has been a very popular feature among Weibull++
users. The Reliability Block Diagram (RBD) feature that has been
added to Version 7 provides a huge leap forward in both flexibility and
analytical power. Now, there is no limit to the number of failure modes
that you can consider and each mode can be analyzed with the appropriate
lifetime distribution. In addition, you can use the flexible RBD
interface (patterned after the intuitive BlockSim diagram utility) to
describe the reliability-wise relationships among the modes (i.e.
series, parallel, k-out-of-n) and thereby model the failure behavior
more accurately and realistically.
Using the exact algebraic reliability
equation for the configuration that you've defined, Weibull++
provides common reliability results and plots at the click of a button.
You can even consider the uncertainty of the fitted parameters of each
data set to calculate confidence bounds on the overall reliability
metrics!
The integrated Diagram utility creates a "block" for each calculated
data set in the project and allows you to build simple or complex
Reliability Block Diagrams (RBDs) to describe the reliability-wise
relationships and calculate desired results. [Click
to Enlarge...]
Enhanced
Warranty Analysis Module
New and enhanced features in the popular Warranty Analysis module
include:
- Choice of Data Entry Form:
You can choose to enter data in any of three available formats: 1)
"Nevada" format with quantity shipped and quantity returned per
period; 2) "Times-to-Failure" format with exact times-to-failure for
returned units or 3) "Dates" format with exact manufacturing and
return dates.
- Consider Subset ID: You can
define and analyze data by "Subset ID" to allow for simultaneous
analysis and comparison of different design iterations.
- Consider Warranty Length in
Forecasts: When performing forecasting analyses, you have the
option to specify the Warranty Length, which allows the analysis to
take into account the possibility that failure data was not collected
beyond the warranty period and/or to exclude predicted failures that
fall outside the warranty period.
- Graphical Plots: You can
generate a variety of graphical plots to illustrate your warranty
analysis, including Reliability vs. Time, Unreliability vs. Time, pdf,
Failure Rate vs. Time, Contour, Failures/Suspensions Histogram,
Failures/Suspensions Pie and Failures/Suspensions Timeline. For
forecasted results, an Expected Failures vs. Period plot is also
available. This plot can display forecasted failures as failures per
month, cumulative failures and/or as a percentage of the total
population. Confidence bounds are also available.
Choice of three data entry forms for
warranty analysis. [Click to
Enlarge...]
Support for
Bayesian Statistics
Although previous versions of Weibull++
have dealt exclusively with Classical statistics, Version 7 opens the
door to another school of thought: Bayesian statistics. The premise of
Bayesian statistics is to incorporate prior knowledge along with a given
set of current observations in order to make statistical inferences.
Bayesian methods have been incorporated into Weibull++
7 in two ways:
- Confidence Bounds: The
Bayesian confidence bounds estimation method is now offered in
addition to the Fisher Matrix, Likelihood Ratio and Beta Binomial
methods that were already supported.
- Weibull-Bayesian Model: Now
available as another lifetime distribution option, the
Weibull-Bayesian model considers prior knowledge on the beta parameter
of the Weibull distribution. There are many practical applications for
this model, particularly when dealing with small sample sizes and some
prior knowledge of the shape parameter is available.
Additional Lifetime
Distributions
In addition to the Weibull-Bayesian model described above, Version 7
also provides the following additional lifetime distributions:
- Gamma
- Logistic
- Loglogistic
- Gumbel
Recurrence
Data Analysis
In life data analysis, there are many cases where events are dependent
and not identically distributed (such as repairable system data) or
where the analyst is interested in modeling the number of occurrences of
events over time rather than length of time prior to the first event,
as in distribution analysis. Weibull++ 7
provides both parametric and non-parametric approaches to analyze such
data. The non-parametric approach is
based on the well-known Mean Cumulative Function (MCF). The
Weibull++ module for this type of
analysis builds upon the work of Dr. Wayne
Nelson, who has written extensively on the calculation and applications
of MCF.
The parametric approach is based on the General Renewal Process
(GRP) model, which is particularly useful in understanding the effects
of the repairs on the age of a system. [See a recent
Reliability Edge article for more information...]
Non-Parametric Recurrence Data Analysis
Utility. [Click to Enlarge...]
Event Log
Interface
The software now provides a specialized folio designed specifically to
capture data in an event log format (commonly used in the Machine Tools
and other industries). This data entry sheet captures the type of event, the date/time
when the event occurred and the date/time when the system was restored
to operation. The software then converts this information to
time-to-failure and time-to-repair data that can be analyzed with life data analysis
techniques. The folio provides a number of options to tailor the
analysis to fit your particular requirements, including the
ability to define shift patterns, consider unique system IDs, perform
the analysis at the system, subsystem, assembly or component level, etc.
You can also export the results to
BlockSim for system
reliability, maintainability and availability analyses.
Event Log Interface for entering system
up and down time data. [Click
to Enlarge...]
SimuMatic
With Version 7, Weibull++ integrates the SimuMatic utility (previously
distributed by ReliaSoft as freeware), that can be used to perform a
large number of reliability analyses on data sets that have been created
using Monte Carlo simulation. This utility can assist the analyst 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 intervals, d) better understand
the concepts behind confidence intervals and e) design reliability
tests.
SimuMatic utility to perform multiple
analyses on data sets generated via Monte Carlo simulation. [Click
to Enlarge...]
Risk Analysis
and Probabilistic Design
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, the area of the item is
distributed as well. In order to find the distribution of the area, we
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.
Monte Carlo utility used for risk
analysis and probabilistic design.
Spreadsheet-Based Customized Report Utility and Enhanced Function Wizard
The ability to build customized reports based on your
Weibull++ analyses has been revised
and enhanced in Version 7. You can work in a spreadsheet or report view,
insert calculated results from existing analyses, and much more. The
Report Template feature allows you to create customized reports that can
be applied to any data set. The software also comes with an extensive
array of report templates for analyses designed to determine Optimum
Burn-In Time, Optimum Preventive Replacement, and much more! The
Function Wizard now works more like Excel®
functions, with the ability to type functions directly into cells and
results that are updated automatically when the inputs change.
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Version 7
