Let's explore where the data comes from and how to prepare for analysis. Plus, let's discuss some ways to look at your data initially.

Some of us might have heard of the Weibull distribution. Some of us might have heard about Weibull analysis. Weibull analysis uses the Weibull distribution to help us visualize failure data in a really useful way. We can see' if our product is wearing out. We can see if our product is wearing in. We can estimate how many things will have failed by certain times. We can do all manners of other wonderful reliability engineering' things through Weibull Analysis. But then there is WeiBayes Analysis.' It combines Weibull and Bayesian analysis ( I know that doesn't mean much to most people). It can be really useful if we know how' something we are testing fails. Because if we do, then we can essentially feed a certain parameter into the analysis to help it on its way. This means that we don't need as much data (always a good thing in reliability engineering). But there are quite a few catches. Interested in learning about Weibayes analysis? Join us for this webinar.
This Accendo Reliability webinar was originally broadcast on 23 January 2024.
To view the recorded video/audio and PDF workbook of the event, visit the webinar page.
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Let's explore where the data comes from and how to prepare for analysis. Plus, let's discuss some ways to look at your data initially.
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The Weibull distribution is a versatile tool to analyze time to failure data. Like any tool, it could be wielded well or not so well.
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A Weibull plot is a really useful way of quickly looking' at data and being able to see' really useful things.
WeiBayes is useful, and there are quite a few catches. Interested in learning about Weibayes analysis? Join us for this webinar.
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