Let's find the motivation to use reliability statistics and find the resources to learn the statistical tools necessary to succeed.

Reliability is a measure of your product or system. Confidence is a measure of you. But we often forget this. We often subject our new product, system, or service to test after test until it reaches this thing called required statistical confidence.' But this is often an illusion, which is great! Because if statistical confidence is often not real' confidence, then we don't always have to resort to statistics to get confidence. In fact, those of us who exclusively rely on statistics are usually those who lack confidence in the product, system or service and need a security blanket to make them feel OK. This webinar talks about confidence from the perspective of the process owner.' The design team lead. The CTO. The junior engineer. And how you can get a much healthier version of confidence through the way we design and produce our things' so that when it comes time to test we are (justifiably) supremely confident that we will absolutely dominate whatever statistical testing hurdle can be thrown our way. And this sometimes means we don't need to deal with statistics at all!
This Accendo Reliability webinar was originally broadcast on 26 July 2022.
Confidence and Tolerance Intervals episode
Confidence from Understanding episode
Choosing a Confidence Level for Test using FMEA episode
Are You Confident in Your Confidence? episode
Does Confidence and Precision Matter in Remote Vibration Monitoring? episode
Let's find the motivation to use reliability statistics and find the resources to learn the statistical tools necessary to succeed.
Let's explore R software's many capabilities concerning reliability statistics from field data analysis, to statistical process control.
Let's explore an array of distributions and the problems they can help solve in our day-to-day relaibility engineering work.
Perry discusses the basics of DOE (design of experiments) and fundamentals so you can get started with they useful product development tool.
Let's discuss the 6 basic considerations to estimate the necessary sample size to support decision making.
When we make a measurement, we inform a decision. It's important to have data that is true to the actual value.
One of the first things I learned about data analysis was to create a plot, another, and another. Let the data show you what needs attention.
If you want a really easy introduction or review of these functions that help inform a decision then check out this webinar.
Sometimes we have to work out how many of them we need (if they make up a fleet) or how many spare parts we need to keep them running.
Let's explore the ways we use, or should use, statistics as engineers. From gathering data to presenting, from analyzing to comparing.
Let's explore what residuals are, where they come from, and how to evaluate them to detect if the fitted line (model) is adequate or not.
This webinar is a light (re)introduction into common mathematical symbols used in many engineering scenarios including reliability.
Reliability is a measure of your product or system. Confidence is a measure of you. But we often forget this.
How to calculate Gage discrimination - the more useful result for a design situation, and even how to use it for destructive tests.
For those who conduct reliability data analysis or turning a jumble of dots (data points) into meaningful information
It is not just a pretty shape' that seems to work, It comes from a really cool physical phenomena that we find everywhere.
Let's examine a handful of parametric and non-parametric comparison tools, including various hypothesis tests.
You need to have a good idea of the probability distribution of the TTF of your product when it comes to reliability engineering.
The post Confidence in Reliability appeared first on Accendo Reliability.