Your Reliability Engineering Professional Development Site
Chris and Fred discuss which liner is best to use on a centrifugal pump, or make a general recommendation. How do you make a recommendation using reliability performance?
ᐅ Play Episode
Chris and Fred discuss how to analyze reliability data for repairable spares—and why the “as good as new” assumption can be dangerously misleading. They explore how maintenance itself can introduce new failures and distort your analysis.
ᐅ Play Episode
Switching systems can be great. The idea is that we can use redundant components to extend the life of a system … and protect the ‘standby’ component from harm until the ‘primary’ component fails. To do this, we need a switch. This often means that we get better reliability than a ‘parallel system’ where both redundant components start wearing out from day one. By protecting the standby component with a switch, reliability can be greatly extended. However, the analysis of a switching system can be challenging. The switch can fail, and the standby component has different reliability characteristics in ‘standby’ and ‘operational’ modes. Many textbooks model switching systems using very basic assumptions to simplify the analysis. But … these assumptions are so inaccurate for most real-world systems that they estimate reliability to be worse than that of a parallel system! This webinar shows you how to model switching (and other complex) systems using Monte Carlo Simulation in Excel … to come up with a ‘perfect’ model to ensure that all that hard work that goes into designing a switching system is not missed by the subsequent analysis! [Read more…]
Amazing products are 90 % identical to mediocre products. It is that last 10 % where failures, forgotten features, overlooked interfaces, and all manner of other things reside. FMEAs and FMECAs are tremendously powerful tools (when done right) at finding the ‘vital few’ things you can address in your first and early design iterations that make everything else that follows a breeze. FMEAs and FMECAs are also awful (when done wrong), as they waste everyone’s time, create no meaningful design guidance, and are just forced upon the tragic few. Then there is AI … which promises to do it all for us! This is not the case. Beyond what standard ‘ISO/IEC 23894:2023 – AI and Risk Management’ says you can and can’t do, AI can only help you get on top of that 90 %. That 90 % is absolutely essential – but at best, AI can quickly get you to mediocre. It is the human brain that takes care of the rest. This webinar gives you 10 reasons why you should do FMEAs and FMECAs properly – and use AI to accelerate getting on top of that 90 % so you can focus on that amazing new product.
[Read more…]
Chris and Fred discusshow to set up a new reliability team—and why structure matters far less than culture. They explain how to focus on decisions, not tools, and how to deliver quick wins that actually improve outcomes.
ᐅ Play Episode
Chris and Fred discuss the “build, test, fix” approach—and why it often leads to poor reliability outcomes when misunderstood. They explain why testing should generate insight, not act as a late-stage safety net.
ᐅ Play Episode
Chris and Fred discuss whether reliability engineers need to learn statistics—and why the real value lies in understanding what the numbers actually mean. They explain how statistics can clarify decisions, prevent costly mistakes, and cut through bad analysis.
ᐅ Play Episode
Chris and Fred discuss electric vehicle (EV) charging stations … and what we can learn about how the industry does well (and not well) when it comes to reliability.
ᐅ Play Episode
Chris and Fred discuss the role redundancy plays in an organization’s culture … especially one that needs to maintain redundant systems and plants.
ᐅ Play Episode
Isn’t reliability prediction a very important part of what reliability engineers should do? Shouldn’t we want to (for example) predict the improvement in warranty reliability a design change will make? Well … yes! But then there is ‘parts count reliability prediction.’ As is the case for lots of reliability engineering terms, there are phrases that are used to describe very specific types of concepts. And ‘parts count reliability prediction’ is awful. And in this webinar, we will explain why … using dogs! If this intrigues you … see you there!
[Read more…]
FMEAs are like diets. There is the ‘5-bite diet’ (no need to explain this one too much) that is so simple to understand, easy to initially say ‘yes’ to, but demonstrably impossible to maintain (bordering on dangerous). Then there is the ‘werewolf diet,’ which appeals to our inner hunter-gatherer that we think we still are, but beyond that, it makes no nutritional sense. There are diets that work well for one person and not well for another. And finally, there is usually (barring medical conditions) a perfectly feasible, sensible, sustainable diet that can work for you if it is tailored to your needs, physiology, and goals.
The reality is that we cannot be truly healthy without a ‘perfect’ diet that works for us. There could be more than one ‘perfect’ diet. There are plenty of ‘mediocre’ diets. And lots of ‘terrible’ diets.
If you are with me so far … welcome to the world of FMEAs!
[Read more…]
If you Google ‘fault tree analysis’ (which I know you probably haven’t), you’ll get a horrible definition that goes something like …
… a fault tree is a deductive failure analysis tool that uses Boolean logic to combine a series of lower-level events to understand the probability of a top-level system failure …
This is technically correct. Unfortunately, definitions like this don’t really help anyone. They make fault tree analysis or ‘FTA’ sound like some abstract math exercise, when in practice, fault trees are one of the most practical and human-friendly tools we have to help solve a huge range of engineering and manufacturing problems. At their core, fault trees are a way of collecting our thoughts, visualizing brainstorming sessions, and structuring messy ideas in a way that helps us make sense of what starts out as being hugely complex problems.
[Read more…]
Most customers aren’t happy with products that break down a lot.
Product unreliability has been behind a lot of losses, cancellations and bankruptcies. A great example is the Yugo – a small, inexpensive car from the former Yugoslavia that gained notoriety in the 1980s and 1990s. It was about half as expensive as similar cars when it hit the US market. And despite a lot of initial ‘excited’ purchasers, it simply stopped selling when people realized how comically unreliable and unsafe it was.
Now there is Rivian. When Rivian burst onto the electric vehicle (EV) scene, it quickly gained a devoted following. The Rivian R1T truck and R1S SUV were praised for their funky designs and innovative features. Owners and enthusiasts love the company’s approach to off-road lifestyles, reinforced by early partnerships with Amazon and promises of building a nationwide ‘outdoor-centric’ charging network.
[Read more…]
In the world of reliability engineering, few tools are as powerful – or as misunderstood – as Weibull analysis. It is a statistical tool, which can turn people ‘off’ straight away, as we can immediately leap to a list of equations and tables of numbers that we need to memorize and embrace. But Weibull analysis is different. You actually don’t need equations.
Check out the chart below, which is called a ‘Weibull plot.’ The different shapes and colours representing the failures of different components can tell us so many things without having to evaluate a single equation.
[Read more…]
Modern militaries don’t win many wars these days. The most dominant, well-funded, highly-trained armies have consistently lost (or at least not won) the Korean War, Vietnam War, Afghanistan War, arguably the Iraq War, and plenty of others. And many dominant, well-funded, highly-trained companies are consistently spitting out unreliable or unimaginative products that smaller and less dogmatic companies have no problem bettering.
To understand why, let’s look at a man called Robert McNamara.
[Read more…]