Your Reliability Engineering Professional Development Site
Chris and Fred discuss what it means (as a reliability engineer) to try and change something … even though the organization that thinks they are open to change really isn’t. What can we do?
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Reliability is a measure of your product or system. Confidence is a measure of you. But we often forget this. We often subject our new product, system, or service to test after test until it reaches this thing called ‘required statistical confidence.’ But this is often an illusion, which is great! Because if statistical confidence is often not ‘real’ confidence, then we don’t always have to resort to statistics to get confidence. In fact, those of us who exclusively rely on statistics are usually those who lack confidence in the product, system or service and need a security blanket to make them feel OK. This webinar talks about confidence from the perspective of the ‘process owner.’ The design team lead. The CTO. The junior engineer. And how you can get a much healthier version of confidence through the way we design and produce our ‘things’ so that when it comes time to test … we are (justifiably) supremely confident that we will absolutely dominate whatever statistical testing hurdle can be thrown our way. And this sometimes means we don’t need to deal with statistics at all!
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Chris and Fred discuss the seemingly never resolved question on ‘who’ is responsible for making something reliable? Is it the supplier? The designers? The manufacturers? Aliens?
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OK … we have all been there. We have all sat in some statistical presentation or read a document containing mathematical symbols and statistical hieroglyphics we don’t understand. And we pretend we do understand so that we don’t embarrass ourselves. The people we don’t want to embarrass ourselves in front of usually also pretend to understand those symbols and hieroglyphics. This webinar is a light (re)introduction to common mathematical symbols used in many engineering scenarios … including reliability. [Read more…]
Chris and Fred discuss what this term ‘confidence’ means … especially when it comes to statistics (and reliability)
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Chris and Fred discuss ‘regression metrics’ … or numbers that software packages spit out at us to suggest if a statistical model is ‘good’ or not. But if this is the only thing you (as an engineer) rely on to understand your system … you are already in trouble!
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Chris and Fred discuss the limits of ‘technology solutions’ … especially when it comes to reliability – mainly because there is always a human being involved!
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Most humans can be quite technically minded. And sometimes we aren’t. Sometimes, we expect every drug or medical procedure to be checked, approved, validated, and tested on other people (et cetera) before subjecting ourselves to whatever our doctor suggests. At other times, we spend lots of money at casinos (note that I said ‘spend’ and not ‘invest’ or ‘win’). When it comes to reliability, we can sometimes be too technically minded. A reliability ‘number’ might not exist until our product has undergone exhaustive testing. Which can often be two years too late to do anything about if it turns out it doesn’t meet all our reliability dreams. So what can we do? Well … why spend money trying to generate information (through lengthy tests) when you can use the information stored in everyone’s brain? The most common answer (even if we don’t want to admit it) is that this sounds like guesswork. And guesswork can sound unprofessional. Or it’s just wrong. But there are ways you can suck out information from a group of experts in a quantifiable and remarkably accurate way. Want to learn more? This webinar introduces you to some of the concepts that might interest you.
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Chris and Fred discuss what it means to have incomplete data. Isn’t data just data?
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Chris and Fred discuss this term we call ‘safe.’ What is ‘safe?’ How can we use the term ‘safe’ in industries that involve a lot of risk? Perhaps there is no such thing as ‘safe?’
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Sounds simple, right? And it is. Reliability growth literally refers to a process where we improve the reliability of a product, system, or service. But sometimes we find ourselves in situations where it is expected that not only do we understand reliability growth … but measure it. And predict how much it will grow in the future. This is sometimes called Reliability Growth Testing (RGT), Reliability Growth Planning (RGP), or Reliability Growth Prediction. And there are lots of equations and models for all these things. But do these models actually model the ‘real world?’ … can they work for you? … SHOULD they work for you? This webinar introduces you to the topic of reliability growth (both qualitative and quantitative) along with key concepts (like the Duane Failure Pattern) to help you work out if there is (or is not) a place for reliability growth in your organization.
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Chris and Fred discuss the ‘hierarchy’ of reliability engineering. Which is the hierarchy of the knowledge and terms we need to follow when we learn about reliability engineering. Is it possible to organize our thoughts in a better way?
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Chris and Fred discuss the terms ‘accuracy’ and ‘intervals’ … which are used a lot by reliability engineers. And how they relate to ‘confidence.’ So what to do any of these terms mean?
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Chris and Fred discuss what ‘reliability growth’ means? Sounds simple … right? And it can be. But sometimes not.
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Chris and Fred discuss what are often seen as competing/different/complementary/friendly/unfriendly disciplines … systems and reliability engineering. How does one relate to the other?
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