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 Weibull Analysis Software - WeibullPro Version 2.0

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weibull analysis software, weibull distribution Functional Overview

The Weibull-Pro computer program analyses failure and repair data by assigning probability distributions which represent the failure or repair characteristics of a given failure mode. Weibull-Pro analyses time-to-failure and time-to-repair data using the following distributions :

  • 1-Parameter Weibull Distribution
  • 2-Parameter Weibull Distribution
  • 3-Parameter Weibull Distribution
  • Exponential Distribution
  • Lognormal Distribution
  • Normal Distribution

    Weibull-Pro automatically fits the selected distribution to the data provided and displays the results graphically in the form of cumulative probability plots, unconditional probability density plots and conditional probability density plots. The plots may be viewed on the screen or printed to a report together with the data on which the distribution is based.

weibull analysis failure mode Different Failure Modes

Separate distributions may be used to represent data originating from different failure modes of the same component. Users may simply tag data items which correspond to different failure modes and request Weibull-Pro to automatically fit a separate distribution to each failure mode in turn. Weibull-Pro also handles censored data.

ease of use Ease of Use

Data may be entered manually by the user or imported from other packages in the form of comma delimited files.

Weibull-Pro has been designed to be extremely easy to use. For example new data can be analysed in 4 simple steps :

  • Enter or import the data
  • Select a distribution type
  • Instruct Weibull-Pro to analyse the data
  • Print a report

ease of use Latest Version

The latest version of WeibullPro Version 2.0 contains many new features including Mixed Weibull analysis capabilities, improved graphing and reporting facilites and many more features. AvSim+, our availability simulator, also contains a fully integrated Weibull Analysis capability. This will allow comprehensive Reliability-Centered Maintenance Models to reflect living field and test data.