Your Reliability Engineering Professional Development Site
When I was a bright eyed, motivated (younger) officer in the Australian Army, one my many tasks when deployed overseas was to raise paperwork to formally request ‘battlefield material’ to be sent back home from whatever country we were in. ‘Battlefield material’ was items that included a range of mementos, keepsakes, and things you would typically see in a museum to add to the historical collections of my battalions and regiments back home.
Chris and Fred discuss the three-letter acronym ‘MLE’ stands for? Well, it stands for ‘maximum likelihood estimate.’ Ever heard of it? Do you know what it means?
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For thousands of years, doctors treated virtually every skin ailment by ‘letting’ or draining the blood of the patient. Leeches are really good at doing this as they quite literally drink up the allegedly ‘poisoned’ blood that is being removed. Of course, by the late 1800s, science had advanced to the point where it was realized that this was nonsense, and so leeches fell out of favour in the world of medicine.
But that same scientific revolution saw the development of drugs like heroin and cocaine to cure everything from schizophrenia through to children’s cough. With doctors prescribing these drugs left right and centre, and worldwide epidemic of drug-addiction misery was spawned.
[Read more…]It is no small irony that a software application that is designed to protect IT systems from malicious actors was behind the biggest IT outage in the history of computers. A company called Crowdstrike provides a ‘Falcon Sensor’ product that is intended to scan computers that use Microsoft operating systems for vulnerabilities. And this product is deployed so deeply into its host operating systems that it has access to the ‘kernel,’ which is the program that runs the basic code that links applications to the computer hardware (like memory, central processing unit and other devices). Unfortunately a Falcon Sensor update that Crowdstrike sent to its customers had a bug that was not picked up by its own validation programs (because it too had a bug). And unfortunately, it accesses a ‘forbidden’ part of the memory that causes the infamous BSOD or ‘blue screen of death.’ So airlines, hospitals, banks, hotels and lots of other companies simply couldn’t operate.
How heavy should you be? Perhaps this is a sensitive question. The average weight of a human is about 65.2 kg or 143.7 lbs. So if your weight is above this figure, are you ‘too heavy’? Conversely, if you are below this figure, are you ‘too light’? Being over and underweight can bring a whole raft of health consequences.
Hopefully you would agree with me in saying that the ‘average’ human weight is not a good benchmark to use if you want to get healthier. Or at least it is not the only benchmark you should think about.
But unfortunately … many manufacturers use approaches that are embarrassingly close to this ridiculous approach to continual improvement.
Some of you might have heard of the Weibull distribution. It is an uncannily accurate way of describing many of the ways components fail. It can model things that wear-in where failure is caused by pre-existing damage and defects in a fraction of products. The Weibull distribution can also model things that wear-out we failure is caused once enough damage has accumulated. And some of you might have heard of the ‘3 Parameter Weibull distribution.’ But what makes this different and (sometimes) helpful? We are always wanting to improve the way we model things, including failure processes. So, to see if the ‘3 Parameter Weibull Distribution’ can help you … join this webinar!
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Chris and Fred discuss reliability prediction and how it can relate to the ‘design’ phase when there is no data. How do you ‘predict reliability?’
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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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