Weibull++ Non-Parametric RDA Data - Revision history

Richard House: Redirected page to Template:WebNotes/Weibull++Non-Parametric RDA Data

2015-07-10T16:20:08Z

Redirected page to Template:WebNotes/Weibull++Non-Parametric RDA Data

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2013-05-20T19:09:31Z

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	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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Richard House at 17:13, 21 February 2013

2013-02-21T17:13:17Z

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Chris Kahn at 11:10, 26 July 2012

2012-07-26T11:10:59Z

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Athanasios Gerokostopoulos at 00:06, 9 May 2012

2012-05-09T00:06:32Z

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Nicolette Young at 16:34, 12 April 2012

2012-04-12T16:34:31Z

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Nikki Helms at 23:42, 22 March 2012

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Nikki Helms at 23:40, 22 March 2012

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Nikki Helms at 23:33, 22 March 2012

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Nikki Helms at 23:28, 22 March 2012

2012-03-22T23:28:54Z

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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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