A Discussion on Weibull Analysis with Fred Schenkelberg

This episode of the weekly podcast discusses the basics of Weibull analysis and distribution technique. By using it you can precisely calculate the probability of failures through a statistical analysis of the failure data. As it is a statistical way of calculating the failure rate and getting an idea about the downtime and life of the equipment, it needs data.

This data is then plotted in the form of a graph whose slope values tells us about the results of our analysis and gives us an estimate about issues and problems that can arise. The widely used software for Weibull analysis is Weibull++. There are many alternatives available for this purpose and one of the good ones is Minitab which works same as Weibull++. There are multiple columns available for each formula available in the package. You have to enter these initial values and the formula takes care of the plot after calculating the slope of the graph. This slope value is then used in calculating the arithmetic means, variations, and regressions of the input data.

The basic features of Weibull are,

• It tells us about the life of the equipment by analyzing the input reliability data obtained from different sources.
• This data is then distributed using different models available in the package library of the software under different failure modes such as exponential, normal, Betta, Gemma and so on.
• There are tools that run reliability and warranty tests. Then, calculate the results using the probability function. The shape is determined by the Betta value in the lifetime function represented by f(t).
• These results are then plotted on a graph which has probability failure values on the Y-axis and life-time failures of the equipment on the X-axis. This is called a 2-parameter Weibull distribution. The slope of these parameters tells us whether the assumptions were Weibull or not. The shape of this plot gives us information about our data flow.
• These results then formulate a statistical reliability data analysis report. This final report then tells the reliability management department about the performance of their equipment in its warranty period.

This Weibull++ software helps you then in forecasting a lot of things such as,

• How will the equipment perform during its life-time?
• Whether an item meets the specifics of the reliability requirements or not?
• To what extent the results differ from the manual provided by the OEMs?

This analysis may not be as effective as RCM or FMEA. But, it saves money and time that is consumed in performing such detailed reliability checks. That is why Weibull probability analysis is used extensively for better estimation of failure rates and required maintenance calculations. But, for getting precisely accurate results, failure data needs to be collected from all the possible sources. This keeps the graphical result line as straight as possible, because more values mean, more points on the graph which makes it easy to calculate the approximately correct results.

References:

• Weibull Distribution (article)
• The New Weibull Handbook
• Accendo Reliability
• Fred Schenkelberg
• www.Reliability.FM
• FMS Reliability
• Weibull++ by Reliasoft
• Minitab

16 – A Discussion on Weibull Analysis with Fred SchenkelbergJames Kovacevic

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