Making Use of Reliability Statistics

If you and your team want to make better decisions with fewer errors or mistakes, then use the appropriate set of tools to gather and understand the data. Let the data inform you.

Mastering the statistical tools related to reliability engineering allows you to master reliability. Identify, characterize, understand, predict, and improve reliability all require statistics. Let’s discuss how it works and 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. Given nearly everyone truly enjoyed their undergraduate probability and statistics course, let’s start the discussion on essential elements of reliability statistics.
Understanding when something will likely fail provide real value to the design team and 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, to characterize variability, and to make decisions. We use statistics to create reliable products. Let’s review a couple of case studies where reliability statistics made the difference.
Let’s explore maintenance planning for a fleet of escalators. Then let’s examine a 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, plus find the resources to learn the statistical tools necessary to be successful.

Fred Schenkelberg, IEEE Reliability Society Evening Meeting, Santa Clara, CA May 7th 2015.

Here’s the presentation.

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