Limits of Block Diagrams
Abstract
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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Author of Reliability in Emerging Technology, multiple books, co-host on Speaking of Reliability, and speaker in the Accendo Reliability Webinar Series.
This author's archive lists contributions of articles and episodes.
by Christopher Jackson 2 Comments
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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by Christopher Jackson 2 Comments
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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by Christopher Jackson 2 Comments
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.
by Christopher Jackson 2 Comments
The Mean Time Between Failure (MTBF) appears in lots of textbooks and standards, so it must be really important … right? Well, not really. The MTBF is the most overused and misunderstood term in reliability engineering, including system reliability modeling, where we can find textbooks and standards with equations that allow you to calculate system MTBF from component MTBFs. If you are unsure why the MTBF is bad, especially for system reliability modeling, then join us for this webinar, where we will illustrate with pictures (not equations) what the MTBF is and how bad it can be to focus on it as a reliability performance metric.
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Chris and Fred discuss how you go about forecasting returns … and understanding things like warranty reliability for products that are ‘shipped all over the place? … at different times? Sound familiar?
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Chris and Fred discuss what happened during the ‘2017 Atlanta Airport Blackout’ where power was lost for 11 hours, hundreds of flights had to be diverted, passengers needed to be housed in hotels, and lots of other costly things. Surely this was due to some sort of unforeseeable event bordering on the ‘supernatural?’ Nope. Not even a little bit.
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Boeing has somehow managed to make the bad public relations created by those pesky onboard batteries catching fire in 2013 practically disappear. Not through good management. But through a never-ending series of disasters and catastrophes that shows no sign of letting up which is dominating Boeing’s news cycle that there is no remaining airtime for missteps like those battery fires.
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Apple recently did something that it isn’t in the habit of doing. And that is – admitting failure. After spending $ 10 billion on ‘Project Titan’ whose aim was to produce a ‘really cool car,’ Apple decided to pull the pin and cancel it.
Simplifying Apple’s Project Titan ambitions to something as pithy as creating a ‘really cool car’ might seem a little condescending. The problem for Apple was that unfortunately, this was the practical truth. And that is why it failed.
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We often use the term ‘system reliability modelling’ to describe any scenario where we need to somehow convert what we know about component reliability into system reliability in order to make a decision. Some of us might have heard of ‘series systems’ that have no redundant components, meaning that the system fails when any component fails. Then there are ‘parallel systems’ where the system fails when the last component fails. But then there are ‘K out of N’ systems that need ‘K’ components out of a total of ‘N’ components to work for the system to work. Do you know when ‘K out of N’ system reliability looks like series system reliability? … or parallel system reliability? … or perhaps you don’t know what series or parallel system reliability looks like? Then this webinar is for you.
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Chris and Fred discuss the similarities and differences between two terms that many people think mean the same thing.
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Chris and Fred discuss a listener’s question about dealing with different ‘duration’ metrics for their field data … so how do we find things like ‘operating time’ and other age-related metrics that aren’t calendar time that simply aren’t there?
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We like to think we make decisions based on information. We don’t. We make decisions based on emotions. And the most important emotion we rely upon for decision-making is confidence. We can be provided all the information in the world, but if we can’t understand it, trust it or believe it, we look for confidence in other ways. Often to disastrous outcomes.
The number of ‘well-funded’ production efforts full of ‘very smart people’ that routinely generate expensive but unreliable products is sadly, very high. And it all comes down to the wrong types of confidence that well-paid decision-makers chase.
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Chris and Fred discuss the importance of being helpful when it comes to reliability engineering. After all, it is much easier to have people want to come to you as opposed to forcing them to do something they don’t want to. To be influential is to be helpful.
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