Your Reliability Engineering Professional Development Site
A listing in reverse chronological order of articles by:
After conducting a thorough root cause analysis and identifying the underlying issues behind a problem, the next critical step is developing and implementing effective solutions. However, this process requires careful planning and consideration of various factors to ensure the solution addresses the root cause and can be successfully deployed. This article explores key considerations when implementing solutions, particularly for products already in the field.
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The 5 Whys technique is a powerful tool for root cause analysis, originally developed by Sakichi Toyoda and later popularized by Taiichi Ohno within the Toyota Production System. This method involves asking “why” five times to drill down to the root cause of a problem, rather than just addressing its symptoms. In the context of product development, particularly in the automotive industry, the 5 Whys approach can significantly improve overall reliability by uncovering the true sources of failure modes.
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In the field of reliability engineering, distinguishing between correlation and causation is essential for accurately identifying the root causes of system failures and ensuring the reliability of engineered systems.
Correlation refers to a statistical relationship between two variables where changes in one variable are associated with changes in another. However, this relationship does not imply that one variable causes the other to change. For example, an increase in ice cream sales and shark attacks are correlated because both increase during the summer, but one does not cause the other.
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The importance of failure repeatability lies in its role in understanding and improving systems, processes, and products. Failure repeatability refers to the consistency with which a system or device can reproduce an outcome under unchanged conditions.
In the context of product design, engineering, and testing, being able to consistently replicate a failure means that the underlying cause can be more accurately identified and addressed.
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In the bustling Boeing factory in Seattle Engineers work diligently on the 737 Max. Alex Carter an engineer notices discrepancies in the AOA sensors test results. His concerns are overlooked amid the pressure to meet production deadlines. In a Sleek boardroom, senior executive Mark Thompson stresses the importance of production targets. Discussions over the MCOS system reveal it relies on a single AOA sensor prompting safety Advocate Sarah Lee to voice her concern.
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I generally write articles about topics I personally struggled to understand from the sources available to us, such as books, online resources, and so on. I believe most technical concepts are fairly straightforward at their core, but the way we express ideas and translate our understanding into writing often makes them harder for others to grasp. That is an area where we can all continue to improve.
As part of that journey, my goal with the Breaking Bad for Reliability newsletter is to be a communicator of Reliability Engineering principles, and I am doing this mainly for two categories of people:
To design more reliable electromechanical components and delay wear out, several strategies can be employed, focusing on material selection, design principles, and reliability testing.
– Hardness: Selecting materials with high hardness can resist wear from abrasion and erosion. For example, ceramics like alumina (Al2O3) and silicon carbide (SiC) are highly resistant to wear and are suitable for components exposed to abrasive environments. [Read more…]
FMEAs are like diets. There is the ‘5-bite diet’ (no need to explain this one too much) that is so simple to understand, easy to initially say ‘yes’ to, but demonstrably impossible to maintain (bordering on dangerous). Then there is the ‘werewolf diet,’ which appeals to our inner hunter-gatherer that we think we still are, but beyond that, it makes no nutritional sense. There are diets that work well for one person and not well for another. And finally, there is usually (barring medical conditions) a perfectly feasible, sensible, sustainable diet that can work for you if it is tailored to your needs, physiology, and goals.
The reality is that we cannot be truly healthy without a ‘perfect’ diet that works for us. There could be more than one ‘perfect’ diet. There are plenty of ‘mediocre’ diets. And lots of ‘terrible’ diets.
If you are with me so far … welcome to the world of FMEAs!
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The Mars Climate Orbiter was a NASA spacecraft launched on December 11th 1998 as part of the Mars Surveyor ’98 program. Its primary mission was to study the Martian climate and atmosphere, map surface changes, and act as a communications relay for the Mars Polar Lander. The Orbiter aimed to monitor daily weather and atmospheric conditions record surface changes and search for water evidence to better understand Mars climate history. Unfortunately, a unit conversion error led to its destruction upon entering Mars atmosphere in September 1999.
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If you Google ‘fault tree analysis’ (which I know you probably haven’t), you’ll get a horrible definition that goes something like …
… a fault tree is a deductive failure analysis tool that uses Boolean logic to combine a series of lower-level events to understand the probability of a top-level system failure …
This is technically correct. Unfortunately, definitions like this don’t really help anyone. They make fault tree analysis or ‘FTA’ sound like some abstract math exercise, when in practice, fault trees are one of the most practical and human-friendly tools we have to help solve a huge range of engineering and manufacturing problems. At their core, fault trees are a way of collecting our thoughts, visualizing brainstorming sessions, and structuring messy ideas in a way that helps us make sense of what starts out as being hugely complex problems.
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The duty cycle of a fuel cell engine, particularly in the context of acceleration and deceleration of a vehicle, is a critical aspect that influences the performance, efficiency, and longevity of the fuel cell system. Understanding the effects of these dynamic conditions on fuel cell engines is essential for optimizing their operation and addressing potential challenges.
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Most customers aren’t happy with products that break down a lot.
Product unreliability has been behind a lot of losses, cancellations and bankruptcies. A great example is the Yugo – a small, inexpensive car from the former Yugoslavia that gained notoriety in the 1980s and 1990s. It was about half as expensive as similar cars when it hit the US market. And despite a lot of initial ‘excited’ purchasers, it simply stopped selling when people realized how comically unreliable and unsafe it was.
Now there is Rivian. When Rivian burst onto the electric vehicle (EV) scene, it quickly gained a devoted following. The Rivian R1T truck and R1S SUV were praised for their funky designs and innovative features. Owners and enthusiasts love the company’s approach to off-road lifestyles, reinforced by early partnerships with Amazon and promises of building a nationwide ‘outdoor-centric’ charging network.
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Generally speaking, pushing value through functional silos usually creates inefficiencies, low buy-in, and a lack of ownership. Resistance to change is almost guaranteed, not to mention the problems caused by missed or poor communication. The same applies to reliability engineering activities during product or process development, which often face strong resistance from design teams, to say the least.
In my 12 years of reliability experience, I’ve seen that reliability engineering is often viewed as just another function — another group asking designers to do extra work because their “baby” (design) is “ugly.” This mindset exists largely because traditional engineering education focuses more on how things function given the boundary conditions, not how they degrade, specifically, how they degrade over time. Let me explain.
Meantime between failures MTF is a widely used reliability metric in various Industries, particularly in electronics and manufacturing. While it can be a valuable tool in certain scenarios, its misuse or misinterpretation can lead to costly mistakes. Let’s explore when MTBF is applicable and when it might be inappropriate to use.
By understanding when to use MTB and when to seek alternative methods, organizations can make more informed decisions about product design, maintenance strategies, and reliability improvements, ultimately leading to better products and more satisfied customers.
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In the world of reliability engineering, few tools are as powerful – or as misunderstood – as Weibull analysis. It is a statistical tool, which can turn people ‘off’ straight away, as we can immediately leap to a list of equations and tables of numbers that we need to memorize and embrace. But Weibull analysis is different. You actually don’t need equations.
Check out the chart below, which is called a ‘Weibull plot.’ The different shapes and colours representing the failures of different components can tell us so many things without having to evaluate a single equation.
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