ReliaSoft Weibull++

If you are not sure which model is appropriate for a given data set, the convenient Distribution Wizard automatically performs several types of goodness-of-fit tests (Kolmogorov-Smirnov, Correlation Coefficient, Likelihood value) in order to rank the available distributions.

The tool also comes with the ability to rank data points using Kaplan-Meier or Median Ranks.

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.

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.

Options include nevada chart, times-to-failure, dates of failure and usage (e.g., mileage, cycles, etc.) as well as time.

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.

Options include Taguchi robust designs, response surface method designs and DOE based on product life (Reliability DOE).

The built-in diagram 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.

A 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.

For life data analysis results and plots include:

• 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”)
• BX% life (i.e., time for a given unreliability)
• Mean life
• Failure rate
• Probability plots and pdf plots
• Contour plots
• Failure/suspension histograms, pie charts or timelines

A custom reporting tool seamlessly integrates spreadsheet and word processing capabilities while enabling you to include calculated results and plots from your analysis.

• 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: The ability to calculate the optimum replacement time 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 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.