| The
latest upgrade to Weibull++,
Version 7, provides many new and enhanced features.
The software is currently under development. A
late summer/autumn release is anticipated.
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 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. |
