Key Features: Industry Standard for Life Data Analysis

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Life data types, distributions, and parameter estimation
Distribution wizard and ranking methods
Confidence bounds
Reliability test design

Warranty data analysis
Degradation data analysis
Reliability block diagrams
Design of experiments (DOE)

Life data results, plots and reports
Related analyses and calculations
Accelerated Life Testing module
Reliability Growth module

Life data types, distributions and parameter estimation

Weibull++ supports all types of life data analysis, including:

Complete (failure time)
Right censored (suspension time)
Left censored
Interval censored
Free-form

Parameter estimation options for standard life data analysis include:

Rank Regression on X (RRX)
Rank Regression on Y (RRY)
Maximum Likelihood Estimation (MLE)
Non-Linear Rank Regression
Fractional Failure Analysis

All major lifetime distributions (including all forms of the Weibull distribution) are also supported:

Weibull
Normal and Lognormal
Exponential
Gamma and Generalized Gamma
Logistic and Loglogistic
Gumbel
Bayesian-Weibull
Mixed Weibull
Competing Failure Modes (CFM)

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Distribution wizard and ranking methods

If you are not sure, which model is appropriate for a given data set, the Distribution Wizard automatically performs several types of goodness-of-fit tests (Kolmogorov-Smirnov, Correlation Coefficient, Likelihood value) in order to rank the available distributions. It comes also with the ability to rank data points using Kaplan-Meier or Median Ranks.

Confidence bounds

Weibull++ provides confidence bounds for parameters, calculated results and plots. Depending on the specific analysis method used, the confidence bounds may be calculated using the Fisher Matrix, Likelihood Ratio, Beta Binomial or Bayesian (BSN) approach.

Reliability test design

Reliability demonstration test design determines the appropriate sample size, test duration or other variables for designing effective reliability tests and demonstration tests. Expected failure times plot displays times-to-failure that you may expect to observe for a given reliability life test.

Difference detection matrix allows you to detect the difference between the reliabilities of two separate designs.

Warranty data analysis

A choice of data entry formats available for using sales/returns data to perform life data analysis and make warranty projections: nevada chart, times-to-failure, dates of failure and usage (e.g., mileage, cycles, etc.), as well as the time.

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Degradation data analysis

Use the linear, exponential, power, logarithmic, Gompertz or Lloyd-Lipow models to extrapolate the failure times of a product based on its performance (degradation) over a period of time. Weibull++ also includes destructive degradation analysis and the option to create user-defined degradation models.

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Reliability block diagrams

The built-in diagram feature allows you to create reliability block diagrams (RBDs) using blocks that are linked to analyzed Weibull++ folios. This feature can be used to analyze complex competing failure modes or simple system reliability. You can even send RBDs built in Weibull++ to BlockSim. This process exports the blocks into a new BlockSim simulation diagram, allowing you to perform further analyses such as system maintainability, availability and related analyses.

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Design of experiments (DOE)

Weibull++ supports a variety of experiment design types, including factorial and fractional designs, Taguchi robust designs, response surface method designs, and DOE based on product life, called reliability DOE.

Life data results, plots, and reports

The Quick Calculation Pad (QCP) is a "Calculation Log" that allows you to record the results from a series of different calculations and then copy/paste the information as needed.

The software also provides a complete array of calculated results and plots based on the analysis. For life data analysis, this includes:

Reliability or probability of failure
Conditional reliability or conditional probability of failure
Reliable life (i.e., time for a given reliability, also called "warranty time")
Probability plots and pdf plots
Contour plots
Failure/suspension histograms, pie charts or timelines
BX% life (i.e., time for a given unreliability)
Mean life
Failure rate

Weibull++ provides a complete array of advanced plotting tools. The Plot Setup allows you to completely customize the "look and feel" of plot graphics. You can save your plots in a variety of graphic file formats for use in other documents.

Overlay Plots (aka Multi-Plots)
Side-by-Side Plots
RS Draw® Metafile Graphics Editor
3D Plots

Customizable reports are also built into Weibull++. They seamlessly integrate spreadsheet and word processing capabilities while enabling you to include calculated results and plots from your analysis.

Related analyses and calculations

Repairable system analysis

Use the General Renewal Process (GRP) model or the Mean Cumulative Function (MCF) to analyze recurrent event data.

Non-Parametric Life Data Analysis

Use Kaplan-Meier, Simple Actuarial or Standard Actuarial techniques when analyzing incomplete data that does not fit any life distribution in a satisfactory way.

Event Log Folio

Use the specialized Event Log Folio to convert system failure and repair data into times-to-failure and times-to-repair.

Monte Carlo simulation

Automatically perform analyses on simulated data sets in order to investigate confidence bounds, testing scenarios and help solve many other reliability engineering questions.

Optimum replacement time calculation

It provides a powerful opportunity to reduce a system's maintenance costs while maximizing uptime. The new Maintenance Planning Tool generates a cost vs. time plot designed to help you determine the most cost-effective time to replace a system’s worn or failed components. The tool also offers an option to create preventive and/or inspection tasks for use in BlockSim’s simulation diagrams.

Non-Linear Equation Fit Solver

Estimates the parameters of any user-defined non-linear equation. This gives you the flexibility to perform simple parameter estimation on statistical models other than the life distributions and life-stress relationship models available in standard folios. After you have solved the equation, the tool provides a plot to visualize how the data fit the function, and also makes it easy to calculate Y for any given X value.

Non-Linear Equation Root Finder

Quickly solves for the root of any user-defined non-linear equation. This helps you eliminate some of the guesswork of solving for the value of the unknown variable that makes the function be as close to zero as possible.

Quick Parameter Estimator

Estimates the parameters of a statistical model based on what you know about the behavior over time. The software will "translate" your answers into the inputs required to obtain the model parameters.

Quick Statistical Reference

Frees you from tedious lookups in tables by quickly returning results for commonly used statistical functions. Results include Median Ranks, Chi-Squared Values, Cumulative Binomial Probability, and many more. There is also a Polynomial Interpolation Function that allows you to enter known data points and then calculate Y for any given X value.

Accelerated Life Testing module

When you purchase the Accelerated Life Testing module, you get new features in Weibull++ designed for accelerated test planning and quantitative accelerated life testing data analysis. The module supports a complete array of utilities for designing accelerated life tests, evaluating the fit of the model, calculating reliability metrics, generating plots and performing related statistical analyses. Additionally, it provides the life-stress relationships required to analyze accelerated life test data with up to 8 simultaneous stress types, where stress is constant or varies with time.

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Reliability Growth module

When you purchase the Reliability Growth module, you get new features in Weibull++. Using reliability growth models, you can analyze data from both developmental testing and fielded repairable systems. During the development phase, you are able to quantify and track the system’s reliability growth across multiple test phases. The module supports advanced methods for reliability growth projections, planning and management.

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