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.

One role reliability engineers enjoy is that of analyzing data. We have available to us a wide range of statistical methods, yet each does require some form of data. In some cases, we are data rich with almost too much data. In other situations, we are lacking data or have insufficient data.
From vendor data sheets to field returns, we do have a broad array of data sources. Let's explore the common and the not-so-common sources. We will discuss the pros and cons of various sources. Plus, let's examine a few ways to use simulations or models.
This Accendo Reliability webinar was originally broadcast on 10 October 2023.
To view the recorded video, visit the webinar page.
Reliability Data and Decisions episode
The Value of Reliability Data episode
Where do I Find Reliability Data? episode
Work Order Data and its Impact on Reliability 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 Reliability Data appeared first on Accendo Reliability.