Let’s talk about how quality and reliability overlap and rely on each other's set of capabilities, plus where we differ.

You may have heard of Statistical Process Control (SPC), 6-sigma, Shewhart, the Japanese Economic Miracle, X̅ – R Charts … or perhaps none of them.

Let’s explore the many ways we use, or should use, statistics in our engineering role. From gathering data to presenting, from analyzing to comparing

The essence of the idea behind the site is to provide our community with great content to help you solve problems, learn, and improve.

how do you go about telling a memorable story about a Weibull plot of field data? Or, a mean cumulative plot of a repairable system?

What is ‘supportability?’ Easy! It’s the ability of your product, system or service to be supported. But how do we get this so wrong so often?

Other than the situation where you build your product inside your customer’s facility, your product will require some form of transportation to move from your factory to your customer.

Then comes the part where 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.

In order to create tests and results that are meaningful we need to both design and execute the test well, then most importantly, interpret the results accurately.

Failure is a random process. But just because something is random, doesn't mean it isn't predictable. A lot of reliability engineering comes down to being able to understand how something fails. And this understanding needs to extend (in some cases) to being able to predict when a certain fraction of things will fail, or how many spares you need. And this means that you need a 'reliability life model.' If you have never heard of them before, or if you want a refresher, this webinar is for you.