Your Reliability Engineering Professional Development Site
Let's have an in-depth discussion during the live webinar series events: Reliability Engineering Basics, Statistics, Accelerated Testing, Program Assessment, and Improvement. Catch up or review past events below.
To attend an upcoming live event, visit the Live Events section of the site, which lists the available upcoming webinars. Recordings are available via recorded videos or audio only via the podcast show.
Find one that looks interesting and register for the event. You will receive login directions and reminders prior to the event. Plus you will be able to join the discussion during the event.
We have many options to learn reliability engineering—books, magazines, newsletters, conferences, seminars, etc. We have options. Some options are better than others, depending on what you want to know. Likewise, some options are better than others, depending on what you want to share.
Sounds simple … right? We simply test faster! Great! But what does this get us? Many organizations are faced with a dilemma when it comes to testing to MEASURE reliability. If we test an amazing new product in ‘at use’ conditions, it might take many years before it will fail. This is time we simply don’t have when it comes to product development. So, how do we test faster? One of the more obvious answers is to increase the stress. Turn the temperature up. Increase the vibration. Use more voltage. But how do we get this right? How can we know that (for example) one week of accelerated testing is equivalent to 10 years of actual use? This webinar will help introduce you to the idea of Accelerated Life Testing, or ALT, to help you and your organization make reliability testing a reality.
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Any product is a collection of materials that have been engineered, shaped, and modified to become components and joints (e.g., weld and braze joints). The materials can degrade due to exposure to use conditions – steel screws corrode when exposed to water, some plastics become brittle when exposed to sunlight, and coatings on surfaces can wear away.
Components and joints will stop functioning as required if their materials degrade too much. This is a problem if it reduces or loses product performance before the end of a product’s expected life.
Identifying the conditions to which materials are exposed and selecting materials that can withstand the exposure are critical parts of designing products that have good reliability.
During this event, I will discuss identifying the conditions that can cause materials to degrade. [Read more…]
Redundancy has continually proven not always to be redundant. Whether the Fukushima nuclear power plant or United Airlines Flight 232, additional components or subsystems that are supposed to take over when others have failed don’t always work. Why is that? There are quite a few reasons … many of which we already know about. But time and time again, otherwise, smart people choose to ignore what we know about how to REALLY make things redundant in order to save costs, save thinking, or otherwise confuse efforts with outcomes. In this webinar, we will look at how redundancy is described in textbooks … and how it can go wrong in the real world.
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The reliability performance of a product or system exists because the decisions that occur during the creation of the product establish how well an item will survive without failure. The choice of material, finish, or technologies, along with all the other decisions involved, define how well a product performs, including its reliability. [Read more…]
Whether new to reliability or a veteran, you have probably heard about the Weibull distribution. It has almost mythical status amongst those who conduct reliability data analysis … or in other words – turning a jumble of dots (data points) into information that actually means something. So why do we ‘worship’ the Weibull distribution? What is so special about it? Whether you have been doing this for a long time or five minutes, you will get something out of this webinar that looks at one of the most popular tools for reliability analysis.
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In my opinion, as I do not know if this is true or not, every product or system failure has a cause. Causes are not exactly the same as what we call ‘failure mechanisms’, yet they are related in many cases. One more term to consider is ‘failure mode’, which refers to the symptoms or results of a failure. [Read more…]
If you have spent any time doing reliability engineering stuff, you will probably have heard of this thing called a ‘fault tree.’ You may have even used fault trees a lot. But it is amazing how many different reliability engineers have different ideas about how to use a fault tree best. Some think fault trees are strictly used to work out which combinations of components need to fail for the system to fail (system reliability modeling). Others think fault trees are really useful for helping us work out what the causes of failure are (root cause analysis). Both people are right. So why do we get these competing schools of thought? Join us for this webinar to learn more about how fault trees can help you … regardless of what you are trying to achieve.
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What is it that makes the difference between good and great related to reliability engineers? What is the magic element that separates those who can carry out tasks such as facilitating an FMEA or designing and analyzing an ALT from those who impact an organization’s culture? A good impact that improves the organization’s ability to create reliable products.
Some of you might have heard about probability plots … like Weibull plots. Some of you might not. A Weibull plot is a really useful way of quickly ‘looking’ at data and being able to ‘see’ really useful things. This could be seeing that a system’s failure rate is decreasing over time … which usually means there are manufacturing defects. It could be seeing that the rate of failure of a system is increasing over time … which means the system is accumulating damage or wearing out. And lots of other things. So, let’s look at a different sort of ‘probability’ plot … and see what we can work out from it. And that means working out what we need to do to improve reliability. Join this webinar if you want to learn how to see really useful things in lines that you might not have appreciated in the past.
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Gage R&R – this is mainly a quality tool, where 10% is a pass and 10-30% is “marginal.” What does that mean, or even better yet, how can I use gage R&R to provide meaningful results in a design environment without specifications? In 30 minutes, we will discuss how you can calculate Gage discrimination – the more useful result for a design situation, and even how to use it for destructive reliability tests.
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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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Both reliability and maintenance activities work to reduce failures and downtime. Perfect reliability of a system would eliminate the need for maintenance. Perfect maintenance would keep even poorly designed (reliability-wise) operating.
Together, the work of reliability and maintenance professionals can achieve more than each team working separately. Each brings a set of insights and skills to the conversation. Working together means improving the design of a system so it’s easier to maintain. It also means the maintenance teams’ day-to-day observations provide meaningful information to the reliability team.
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…]
Disruption has been one of the major news items in 2022. Disruption results in risk. You can see ‘risk’ in almost every video, magazine, and blog. Russia’s invasion of Ukraine. Supply chain disruption. Climate change. New business models. Reshoring. Inflation. Price of gasoline. Can you imagine $10/gallon gasoline?
Greg will answer the following:
What is risk-based, problem-solving, and decision-making in reliability engineering and quality?
What are risk PDCA, taxonomies, risk assessment, risk management, etc?
What are the two critical risk management frameworks for problem-solving and decision-making?
What are examples of risk assessment tools? [Read more…]