Life data analysis
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Description

Support life data analysis (Weibull analysis).

  • support all relevant distributions/models (Weibull, Gumbel, Log-Normal)
  • add template for Weibull plots
  • provide wizard for life data analysis

Links:

sgerlach created this task.Sep 27 2016, 9:52 PM
asemke added a subscriber: asemke.Feb 27 2017, 4:53 PM

Weibull++ (taken from http://wildeanalysis.co.uk/reliability/software/reliasoft/weibull )

  • Weibull++ supports Complete, Right Censored (Suspended), Left Censored, Interval Censored and Free-Form data, entered individually or in groups. A specialised interface to analyze event log data is also available.
  • All Major Lifetime Distributions: The software supports data analysis with the 1, 2 and 3 parameter Weibull, Mixed Weibull, 1 and 2 parameter Exponential, Lognormal, Normal, Generalized Gamma, Gamma, Logistic, Loglogistic, Gumbel and Bayesian-Weibull lifetime distributions. The Distribution Wizard automatically performs goodness-of-fit tests to help you select the most appropriate model for each data set.
  • Warranty Analysis: Perform life data analysis and make warranty projections based on sales and returns data, entered in a Nevada, Times-to-Failure or Dates of Failure format.
  • Reliability Block Diagram: Use Reliability Block Diagrams (RBDs) that are integrated with calculated data folios to analyze competing failure modes and perform other system analyses.
  • Recurrent Events Data Analysis: Use parametric or non-parametric methods to analyze events that are dependent and not identically distributed (such as repairable system data) and/or to model the number of occurrences of an event over time.
  • Degradation 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.
  • Non-Parametric Life Data Analysis: Use Kaplan-Meier, Simple Actuarial or Standard Actuarial techniques for non-parametric life data analysis.
  • SimuMatic: Automatically perform large quantities of analyses on simulated data sets in order to investigate various reliability questions, including confidence bounds, testing scenarios, etc.
  • Design of Reliability Tests: Determine the appropriate sample size, test duration or other variables for reliability demonstration tests.
  • Parameter Estimation: options for standard life data analysis include Maximum Likelihood Estimation (MLE), Rank
  • Regression on X (RRX) or Rank Regression on Y (RRY).
  • Weibull++ also 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 approach.
sgerlach moved this task from Backlog to Current Release on the LabPlot board.May 1 2017, 5:33 PM
asemke moved this task from Current Release to Backlog on the LabPlot board.Sep 21 2018, 9:59 AM