Weibull++ Non-Parametric RDA Data: Difference between revisions

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Non-parametric recurrence data analysis provides a nonparametric graphical estimate of the mean cumulative number or cost of recurrence per unit versus age. In the reliability field, the Mean Cumulative Function (MCF) can be used to: [31]
The non-parametric RDA folio is based on the mean cumulative function (MCF). This analysis provides a plot of the MCF to illustrate the average number of recurring failures of a system, or a group of systems, over a given period of time (or distance, cycles, etc.). The MCF can be used to evaluate whether the number of failures increases or decreases over time, to predict the future number of failures or to compare different data sets from different designs, operating conditions, production periods, etc.
 
:• Evaluate whether the population repair (or cost) rate increases or decreases with age (this is useful for product retirement and burn-in decisions).
:• Estimate the average number or cost of repairs per unit during warranty or some time period.
:• Compare two or more sets of data from different designs, production periods, maintenance policies, environments, operating conditions, etc.
:• Predict future numbers and costs of repairs, such as, the next month, quarter, or year.
:• Reveal unexpected information and insight.
 
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Revision as of 23:28, 22 March 2012

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Non-Parametric RDA Data

The non-parametric RDA folio is based on the mean cumulative function (MCF). This analysis provides a plot of the MCF to illustrate the average number of recurring failures of a system, or a group of systems, over a given period of time (or distance, cycles, etc.). The MCF can be used to evaluate whether the number of failures increases or decreases over time, to predict the future number of failures or to compare different data sets from different designs, operating conditions, production periods, etc.

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