You have come to the home of the Weibull Trending Toolkit, WTT. Suppose you have a set of N measurements. There is a possibility that the statistical distribution of the data can be matched with the distribution represented by the three parameter Weibull distribution function. Glenn Bowie created the software used to find the three parameters by matching the first three statistical moments of the data with three moments of the Weibull distribution. In simpler terms, the mean, standard deviation, and skewness of the data are matched by the mean, standard deviation, and skewness of the Weibull function. The collection of software tools used to achieve the matching relations is called the Weibull Trending Toolkit. You may obtain versions of the Weibull Trending Toolkit at a site hosted by Carnegie Mellon University. See the following quotation: Welcome to StatLib DOS/Windows general collection. StatLib is happy to provide a source for statistical software for the DOS and Window operating environments. StatLib does not have access to a DOS/Window computer, so we can offer no comments about the quality of the software. In particular we do NOT do any checking for viruses. The DOS general archive currently contains: WTT The Weibull Trending Toolkit (WTT) is described and applied in three self-extracting files, WTT01.EXE(52k), WTT02.EXE(484k) and WTT03.EXE(1M) QBasic programs in WTT may be executed from DOS or Windows. Submitted by Glenn E. Bowie (glennbowie@earthlink.net). [10/Jul/00][24/Jul/00] You may obtain the three WTT programs here: http://home.earthlink.net/~glennbowie/WTT01.EXE http://home.earthlink.net/~glennbowie/WTT02.EXE http://home.earthlink.net/~glennbowie/WTT03.EXE Tutorial wtt02.html applies the Weibull Trending Toolkit in a Pitting Corrosion Project. It may be read online at http://home.earthlink.net/~cortechtraining/wtt/. Tutorial wtt03.html applies the toolkit to a study of Fatigue, Fracture, and Crack Growth Data. I commend the Reliabilityweb site to you for references to commercial Weibull software and courseware. Terrence O'Hanlon, Reliabiltyweb site manager, has kindly referred to my Weibull Trending Toolkit.

> January 22, 2001
> I, Glenn Bowie, want plant reliability and maintainablity analysts to stretch a bit and imagine they are investigators. During my airframe industry career I was asked to do just that when called upon to participate in studies of aircraft-on-the-ground (AOG) events. And I want law enforcement forensic analysts to imagine they will be called upon to apply certain plant or other equipment maintainability analysis tools.

> The Union Of Predictive Preventive Maintenance And Vibroacoustic Forensics

> January 24, 2001.

> Task1: Significance of Outliers

> Think of a set of measured times to failure, N. In this example N=10. Apply the Weibull Trending Toolkit (WTT) to the data. WTT yields three parameters of the Weibull distribution, k, e, and v. Parameter k is an exponent, v a characteristic value, and e is a threshold parameter. If e is found to be less than zero when studying life data, there is an implication that failures can occur before an item is put into service. In most practical instances this interpretation of the life data does not make sense. Then examine the lives in the set. If one or more values has or have significant effect on the WTT results there is a possibility that one or more values is an outlier or are Outliers and should be excluded from the set when applying WTT. Your are urged to analyze a particular case at your own speed. I, Glenn Bowie, am willing to help you. To proceed go to http://home.earthlink.net/~glennbowie/ppm_forensic.html.

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