The Reliability FM network

Fundamentals of Metric Monitoring podcast episode with speaker Fred Schenkelberg Following along the idea stated by Lord Kelvin, “…when you can measure what your are speaking about, and express it in numbers, you know something about it…”, we have organizations measuring reliability performance. Not that measuring something is managing it, those are two different activies. […]

Want to understand the only way you should be generating confidence when it comes to reliability engineering?

Let’s discuss a couple of easy ways to accomplish reliability allocation or apportionment then examine a valuable way to use this tool.

Understand the lognormal distribution and its correlation to the bell curve. Harness this understanding to make crucial decisions.

We examine using our knowledge and the knowledge of others to streamline the testing or avoid it altogether.

Let’s explore the range of considerations when designing an ORT to optimize the ORT’s ability to identify field problems efficiently.

Let’s explore the concept of a delta phase and how to implement it in your organization. Plus, how to implement it in various product types.

Electronic component manufacturers use the term ‘Failures in Time’ of ‘FITs’ to describe the reliability of their products. But what is a FIT?

Let’s examine system effectiveness in more detail. Then, examine an example or two so you can apply this concept to your situation.

Understand the difference (if any) between FMEAs and FMECAs? … and How can you make an FMECA work for you?

Let’s explore the elements that make up a reliability goal. Plus, the range of inputs you can use to define each element.

Learn how fault trees can be used for conducting root cause analysis in this informative webinar from Accendo Reliability.

Let’s examine a few principles and tips so you can learn and master what you desire to learn and master.

Some of you might have heard of the ‘3 Parameter Weibull distribution.’ But what makes this different and (sometimes) helpful?

Let’s explore the basics of conducting Pareto Analysis, plus a few different ways to create and modify the plots.

You need to have a good idea of the probability distribution of the TTF of your product when it comes to reliability engineering.

Let’s examine a handful of parametric and non-parametric comparison tools, including various hypothesis tests.

This is where taking a breath and understanding our product before we build the wrong thing fast can really helpful.

Let’s explore the steps necessary to obtain valid and valuable process capability ratios. Then, let’s examine how to use this information.

Sometimes the equations we need to model reliability are just so complicated that we simply avoid them. Let's use Monte Carlo instead.

Statistical control charting (SPC) is a method for monitoring and determining whether a process is in control or stable.

Greg will discuss the critical architecture and design practices that need to be considered in AI product development and deployment.

The Mean Time Between Failure (MTBF) appears in lots of textbooks and standards, so it must be really important … right? Well, not really.

Let’s examine safety margins and why they are one method to design robust products that also improve product reliability performance.

In this presentation, Greg Hutchins will explain how to Get Unstuck: Do Good. Be Happy – based on the Working It book.