Your Reliability Engineering Professional Development Site
I am constantly confronted by students, reliability engineers and other people banging fists on tables and saying …
… 89 percent of failures are random …
Firstly, 100 percent of failures are random. It’s just that there are lots of textbooks and experts telling us that a ‘random’ failure is one that happens irrespective of age. That is, a failure with a constant ‘failure rate’ where the item in question doesn’t appear to age or wear out.
Chris and Fred discuss the difference between good and poor reliability testing.
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We often use probability distributions to help us characterize the likely values a random variable will have. This includes the random variable we call ‘time to failure’ or TTF, which is how long something works before it fails. Failure is a random process, but just because it is random, doesn’t mean it’s unpredictable. Products that wear-in will have vastly different probability distributions for TTF when compare do products that wear-out. So you need to have a good idea of the probability distribution of the TTF of your product when it comes to reliability engineering. But we often see in textbooks and standards the ‘exponential distribution’ simply being assumed as a ‘good’ TTF probability distribution. But is it? And what happens when it isn’t … but you use it anyway? Join this webinar to find out!
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Chris and Fred discuss the problems we experience when we are in an organization with very ‘short-term’ thinking. What can we do?
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Chris and Fred discuss the challenge of being asked by someone to show (or visualize) stunning, eye-popping results for some reliability activity. How do we do this? Is this possible?
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Chris and Fred discuss how short, 1-minute explainer videos could help reliability engineers … especially new ones!
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Chris and Fred discuss what Failure Reporting and Corrective Action Systems (FRACAS) and Computerized Maintenance Management Systems (CSSM) are … and what they are not … and how they relate.
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Many engineers rush to design or build something that we think is ‘awesome’ or at least ‘proves a concept.’ But this often means we build something that we like (not necessarily what our users like) or doesn’t work (because we didn’t realize that have sensitive electronic components near hot exhaust manifolds would be a problem). This is where taking a breath and understanding our product before we build the wrong thing fast can really helpful. A FMEA or functional block diagram can really help us visualize what different parts of our system do, and how they interact. They also help us identify the basic, interface and additional functions that separate an ‘average’ product from an ‘industry leading’ product. If this is something you think you or your team can benefit from, join us for this webinar.
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Chris and Fred discuss why the Physics of Failure (PoF) is hard to model? … or is it?
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Chris and Fred discuss the MTBF … again. And again. People don’t (want to) get it. So here we go again …
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Chris and Fred discuss how we go about modeling the reliability of systems … particularly with things called ‘block diagrams.’ Might this help you?
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Chris and Fred discuss where the ideas of ‘confidence bounds’ come from … and perhaps what they mean.
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Sometimes the equations we need to model reliability are just so complicated that we simply avoid them, or use other equations that are simpler but model the wrong thing (see some of my earlier webinars!). But it doesn’t have to be this way. Monte Carlo simulation is so simple that anyone who has access to Microsoft Excel can use it. What this means is that we don’t need to use complicated equations (like those use to model things like switching systems) and instead can use Microsoft Excel to help us get approximate (but really accurate) answers. Sound interesting? Join us for this webinar!
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Chris and Fred discuss Weibull Analysis and how it can help you can first take your ‘tentative’ steps to learn more about it.
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Many of us like to think that we can, at least sometimes, be objective. Which is the opposite of being subjective.
What does this mean? Something is ‘objective’ if it only depends on the world around it, and nothing else. Like the ‘perfect juror’ who is only swayed by facts and evidence when determining if he or she thinks someone is guilty of murder. Something is ‘subjective’ if it can be influenced … by itself. Like the ‘imperfect juror’ who decides to acquit a murder suspect regardless of the evidence … because the suspect is his or her brother. This is called bias.
