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

Mastering the statistical tools related to reliability engineering allows you to master reliability.
Identifying, characterizing, understanding, predicting, and improving reliability all require statistics. Let's discuss how it works and what will work for you.
Variability causes failures.
From the variability of material properties to use conditions all lead to the uncertainty of when and what will fail. Statistics is the language of variability.
Since nearly everyone truly enjoyed their undergraduate probability and statistics course, let's start discussing essential elements of reliability statistics.
Understanding when something will likely fail provides real value to the design team, the business, and the customer.
We don't use statistics just because it's cool (which it is, btw); we use statistics to reveal problems, characterize variability, and make decisions. We use statistics to create reliable products. Let's review some case studies where reliability statistics made the difference.
Let's explore maintenance planning for a fleet of escalators.
Then, let's examine medical product field data and help the team focus on specific areas to improve the system's reliability.
We'll finish the discussion with a short discussion on the next steps to get started when confronted with some data.
Let's find the motivation to use reliability statistics and find the resources to learn the statistical tools necessary to succeed.
This Accendo Reliability webinar originally broadcast on 3 February 2015.
To view the recorded webinar and slides visit the webinar page.
When and Why Use Statistics episode
Statistics and Reliability episode
Reliability and Statistics 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.
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