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.

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. In this short webinar, let's discuss when and why you would use Weibull analysis, the basic process, and its limitations.
Weibull analysis is very popular and has become a generic term for life data analysis. It is useful, has some nice features, and is easy to interpret. Yet, it has a dark side as well. Let's talk about the basic use of the distribution, when not to use it, and how to know when better tools are available.
A great first step when faced with a pile of data is to plot it. Look at the data and get a sense of what story the data may have to tell. Another early step in any data analysis is to detail what question you are trying to answer. Are you looking for problems that you then can solve? Are you trying to understand the reliability performance of your product? Or something else?
Let's discuss the fundamentals of Weibull analysis, including the basic approach, when and why you would do such an analysis, and some problems that may arise. The idea is to help you understand this tool well enough to wield it confidently as you identify and solve reliability questions.
This Accendo Reliability webinar originally broadcast on 10 April 2018.
To view the recorded video and event slides, visit the webinar page.
Weibull Analysis and Physics Trumps Mathematics episode
A Discussion on Weibull Analysis with Fred Schenkelberg episode
What is Weibull Distribution? episode
Questions to Ask about Data Analysis episode
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.
For repairable items, the mean cumulative function and associated plots provide you with an estimate of the effectiveness of your repairs.
We will discuss the pros and cons of various sources. Plus, let's examine a few ways to use simulations or models.
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.
The design is done, the assembly process is working, now we can focus on answering the question: is the product hitting reliability targets?
Data is only as useful as the information you derive. So would you like to take your Weibull probability plotting skills to the next level?
Minitab itself has many reliability functions available; this presentation covers the basics, including distributions, censoring, and fitting.
This webinar examines an important perspective. Its' so simple and has made many heroes in the data analysis world since Abraham Ward.
Some of you may have heard of Bayesian analysis.' You may think this is something fancy that only universities do.
Let's take a closer look at the concept of likelihood and it's role in an MCMC analysis. A powerful tool for data analysis.
This webinar is about how we use this thing called Markov Chain Monte Carlo Simulation (MCMC) to create this posse.'
We show you how to get your computer to help you give useful reliability information to your boss, manager, director, or whoever.
To create test results that are meaningful, we need to both design and execute the test well, then, interpret the results accurately.
there are ways you can suck out information from a group of experts in a quantifiable and remarkably accurate way.
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.
Sometimes the equations we need to model reliability are just so complicated that we simply avoid them. Let's use Monte Carlo instead.
The post Fundamentals of Weibull Analysis appeared first on Accendo Reliability.