The intent of any failure analysis is to understand the problem well enough to craft and implement short and long-term solutions.
‘parts count reliability prediction’ is awful. And in this webinar, we will explain why. If this intrigues you, enjoy this episode.
Let’s explore a few of the limitations, checks, and options when taking a look at some data. Checking assumptions and more.
Bugs are so common that we know how most of them happen. So we can work out what went wrong to allow that bug to happen.
Let’s explore the range of options available to estimate the life of an item, plus the pros and cons of each method.
Let’s explore when and how to identify which types of environmental testing should be done so that they add value.
So if you want to find out what reliability actually is (no equations) … this webinar is for you! - it's not MTBF, BTW
Let’s examine the success testing approach, the assumptions, benefits and faults. Plus, what other options you may have available
perhaps you want to estimate the reliability of something that is supposed to last a long time, but don’t have a lot of time to test.
Explore the framework to assess equipment reliability for air fin coolers and ensure operational excellence in process plants.
Ever heard of the MTBF? A lot of people have. But not many people (truly) understand what it is.
Let’s explore why derating is important, the difference it can make, and a few methods to implement derating with your design team.
Weibull probability plotting is perhaps the most widespread data analysis tool used in reliability and quality engineering.
Product requirements that have the most impact on customer needs should be considered in your design failure modes and effects analysis (DFMEA)
Reliability engineers are often taught about ‘cut sets.’ But we rarely use them. Many reliability engineers don’t know what they are.
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.