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Speaking Of Reliability: Friends Discussing Reliability Engineering Topics | Warranty | Plant Maintenance
Speaking Of Reliability: Friends Discussing Reliability Engineering Topics | Warranty | Plant Maintenance episodes
- Leaders, Champions, and ManagersLeaders, Champions, and ManagersAbstract
Chris and Fred discuss what a leader, champion and manager are. Many textbooks, guidebooks and so-called ‘domain experts’ tell us what (for example) a ‘reliability leader’ is. In some cases the ‘reliability leader’ is someone who has little influence, and is more of an ad hoc ‘doer.’ Not a leader. Why is this? Listen to this podcast to hear more about this?
Key PointsJoin Chris and Fred as they discuss
Topics include:
- Who is a ‘leader’? Well, it is not (by default) the person who has leadership qualities. It is the person who has executive power and controls resources. And the fact that they may be a poor leader doesn’t mean they are not the leader. It is just that their poor leadership places the onus on their subordinates to pick up any slack. But this won’t produce anything close to ‘optimal’ outputs.
- Can there be a ‘reliability leader’? What do you think? The main issue that Chris and Fred identify is that many organizations designate someone as the ‘reliability leader’ in a way that gives the ‘visage’ of relevance or importance. But … the so-called ‘reliability leader’ often has no power, no authority and no resources. So they quickly evolved into a ‘reliability doer’ who provide a service. Ad hoc tasks done here and there. But only if, the organization asks them to become involved.
- Reliability gardiners. Sounds cool! Fred talks about how (in one case) ‘reliability experts’ … who called themselves ‘gardiners’ … would create ‘local champions’ and ‘local experts’ in programs and groups. They quickly became ‘leaders’ in their domain. But this was accompanied by unwavering support from the organization leaders. So can we call them reliability leaders? Or was the organizational leadership team the ‘true’ reliability leaders because they knew the importance of their gardiners?
- But we need lots of leaders in an organization to work together. So can we call any of these people ‘reliability leaders?’ One thing is for certain is that if the ‘organizational leader’ doesn’t care about reliability, than any lower-level leadership will not overcome that problem.
- This does not mean no one can show ‘reliability leadership.’ Far from it. Everyone can. And in certain cases – must.
- And then there are managers … Who aren’t leaders. A manager takes resources allocated to him or her and work out the most efficient way to realize some goal. But it is the leader who comes up with the vision that drives these goals. Many business ‘leaders’ are actually people who excelled at ‘management’ who were the only ones left when it came time for promotion.
- What about the ‘reliability graybeard?’ The sage who everyone goes to for guidance? If this person is recognized for their excellence in the domain … great! And if senior leaders support this informal relationship where the ‘graybeard’ must be consulted to make a good product … great! For now. Your success is based on your ability to maintain this informal relationship. Which is inherently unstable if your organization is not formally set up this way. Because you have a competing priority that will come completely dominant (one way or another) if a single person leaves your organization.
So what do you think?
Enjoy an episode of Speaking of Reliability. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.
Download Audio RSSShow NotesThe post SOR 548 Leaders, Champions, and Managers appeared first on Accendo Reliability.
0 min - When and Why Around AssumptionsWhen and Why Around AssumptionsAbstract
Chris and Fred discuss assumptions – and when you need to check if they are valid. And if you do need to … how do you check these assumptions? Reliability (and all sorts of other engineers) need to study variation and variance. We are often interested in when the first ‘5 percent’ of things will fail. So assumptions on the underlying failure (or random) process are crucial. Sound familiar? Listen to this podcast to learn more.
Key PointsJoin Chris and Fred as they discuss the many assumptions that reliability engineers are faced with throughout their roles. And these assumptions often revolve around capturing the random nature of a process. Like failure. And this is really crucial because reliability engineers need to know all sorts of metrics and values that are based on the nature of the random process. Things like warranty reliability, mission reliability, and service life reliability are all typically the point by which only a small number of our products or systems have failed. Which is not the average time to failure. So what do you do?
Topics include:
- Software will always give you ‘a number.’ And that number will always be ‘right.’ As in, it will process the data you input into the software and subject it to the algorithm or analysis you select. Which is often the ‘default’ one. Do you know what your software is doing to give you your number?
- Too many people are (1) unaware of their assumptions or (2) ‘hand wave’ until it is OK. Understanding the underlying assumptions is at best a dying art.
- It all comes back to the question you are trying to answer. If you can really define the question well, then the answer to your many questions about assumptions often become really easy to answer. All because you brought your analysis back to the reason you are doing testing or analysis in the first place.
- And sometimes – challenging and correcting your assumptions can be really good for you! In our recent webinar on probability plotting we showed how making an assumption created an upper confidence bound on failure probability of around 90 percent. But – when we removed an incorrect assumption the upper confidence bound on failure probability dropped to 10 percent. That error is huge! And you could have blown out an entire production timeline by simply making an incorrect assumption.
- And you really need to know what the central limit theorem is all about. This simply means that when we add a lot of random variables together, we end up with our stereotypical bell curve. And what this means is that when we have lots of data points our understanding of our ‘confidence’ in key metrics becomes really easy to characterize. But using the central limit theorem is of itself … an assumption! So you need to know when it applies.
- But assumptions don’t just apply to analysis – they apply to activities. How much will a failure mode and effect analysis (FMEA) save your organization? Well, this saving is based on the number of design and manufacturing deficiencies your FMEA team identifies. And also based on how much it costs you if you don’t find out about these deficiencies until ‘late’ in the production process. Can you know this before you do your FMEA? Of course not. But can you make some basic assumptions about how many critical deficiencies you will find and how much their prevention will save? Absolutely. In fact, you can’t do anything in life without some basic assumptions about the likely benefit of that activity.
Enjoy an episode of Speaking of Reliability. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.
Download Audio RSSShow NotesThe post SOR 547 When and Why Around Assumptions appeared first on Accendo Reliability.
0 min - Working Remotely WellWorking Remotely WellAbstract
Carl and Fred discussing ideas about how to maximize effectiveness while working remotely.
Key PointsJoin Carl and Fred as they discuss the pros and cons of remote working and remote teaching.
Topics include:
- Presenting webinars
- Participating or leading meetings from home
- Facilitation skills in remote environment
- What works when working remotely
- What doesn’t work when working remotely
- Teaching remotely
- The role of body language in communication and how to compensate remotely
- Good meeting practices apply to remote environment
- Tips to make remote meetings work better
- Use of questions and answers in remote environment
- Introverts and extroverts in remote meetings
- Making the environment safe for students to ask questions
- Importance of student or audience feedback to assess learning
Enjoy an episode of Speaking of Reliability. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.
Download Audio RSSShow NotesIn this podcast, there was reference to a video segment of a remote interview, with a humorous background distraction. Here it is:
The post SOR 546 Working Remotely Well appeared first on Accendo Reliability.
0 min - What to do with 3 SamplesWhat to do with 3 SamplesAbstract
Carl and Fred discussing what you can do if you only have 3 samples for testing.
Key PointsJoin Carl and Fred as they tell stories about testing with limited numbers of samples, the pitfalls to watch out for, and how to maximize the resulting information.
Topics include:
- Start with test objectives, before determining sample sizes
- Lipson book “Engineering Experiments”
- Weibull plots
- Success-run theorem
- Relationship between sample size, testing time, confidence and reliability
- How many lifetimes can be tested
- Statistics and Engineering both provide input to test planning
- Importance of understanding failure mechanisms
- Bogey testing works best with multiple failure mechanisms
- Samples for HALT
- Where are you in the system hierarchy?
- During product development, track all failures, regardless of when or where they happen
Enjoy an episode of Speaking of Reliability. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.
Download Audio RSSShow NotesThis podcast referenced the following book: Statistical Design and Analysis of Engineering Experiments, by Charles Lipson and Narendra Sheth, published by McGraw-Hill Book Company, 1973
The post SOR 545 What to do with 3 Samples appeared first on Accendo Reliability.
0 min - Potential Long Term Changes to Live Professional DevelopmentPotential Long Term Changes to Live Professional DevelopmentAbstract
Kirk and Fred discussing the changes in professional conferences and seminars due to the worldwide COVID-19 pandemic
Key PointsJoin Kirk and Fred as they discuss how to engineering world, along with all education across the world, has changed due to the pandemic
Topics include:- The pandemic is making many of our systems, such as the internet, stressed to limits.
- Online webinar and podcast for reliability education now during the world pandemic may shift reliance and preference to remote teleconferences and online classrooms
- The current period is a great time to catch up on podcasts and articles at Accendo Reliability to informally learn more about reliability issues and solutions.
Enjoy an episode of Speaking of Reliability. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.
Download Audio RSSShow NotesHere is a link to Kirk’s book co-authored with John J. Paschkewitz available from Amazon “Next Generation HALT and HASS: Robust Design of Electronics and Systems”
Here is the link to the US ARMY/CALCE PAPER presented at the 2013 RAMS conference event mentioned in this podcast– “Reliability Prediction – A Continued Reliance on a Misleading Approach” . This is a government document that is in the public domain and should be distributed a read by any engineer that believes failure prediction methodology is useful or beneficial during product development.
The post SOR 544 Potential Long Term Changes to Live Professional Development appeared first on Accendo Reliability.
0 min - Evaluating a Discreet Component for ReliabilityEvaluating a Discreet Component for ReliabilityAbstract
Kirk and Fred discussing a question on testing of a single transistor for reliability assurance.
Key PointsJoin Kirk and Fred as they discuss a listeners testing a discreet component and the real future causes of failures in systems.
Topics include:- Using a few samples of an inexpensive parts to test to limits (test to failure) to find the real capability and margin in the device.
- Most failures are due to mistakes in design, application, manufacturing which can result in latent defects.
- Testing a singular transistor in a system is not as efficient or comprehensive as stress testing at the system level.
Enjoy an episode of Speaking of Reliability. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.
Download Audio RSSShow NotesHere is a link to Kirk’s book co-authored with John J. Paschkewitz available from Amazon “Next Generation HALT and HASS: Robust Design of Electronics and Systems”
Here is the link to the US ARMY/CALCE PAPER presented at the 2013 RAMS conference event mentioned in this podcast– “Reliability Prediction – A Continued Reliance on a Misleading Approach” . This is a government document that is in the public domain and should be distributed a read by any engineer that believes failure prediction methodology is useful or beneficial during product development.
The post SOR 543 Evaluating a Discreet Component for Reliability appeared first on Accendo Reliability.
0 min - Setting Up to Report Monthly Failure RatesSetting Up to Report Monthly Failure RatesAbstract
Chris and Fred discuss how we need to estimate monthly failure rates of a product. Like when bosses or directors want to know what the ‘failure’ or ‘return’ rate of a product is this month. But is this useful? How do we account for the number of products we have shipped? How old are the products when they fail? And how do we learn from these numbers? Can we even find a number? Listen to this podcast to learn more.
Key PointsJoin Chris and Fred as they talk about monthly failure rates. So let’s say we get 20 returns in the first year of a product launch where we shipped 500 products. Is this good? What if we get another 20 failures in the second year where we ship another 1 000 products. So we now have a total of 40 failures over 1 500 products. Do we average these figures? Is there anything we can use these numbers for? The first thing you need to know is what you are trying to do or inform.
Topics include:
- You do need to know how much you are spending on returns this month. This is a simple accounting or business requirement. You need to know how much you are spending, are going to need to spend and so on. You can’t escape this.
- But if you want to know why your products are failing or if you will meet your warranty goals – you need to do more. And basic failure rates won’t help answer this question. You need to know other things like how old your products were when they failed. If your warranty period is based on usage – how many cycles had your products accumulated before they failed? It is all about the
- And another thing – returns versus units out this month doesn’t work. Let’s say this month you shipped 17 000 products this month – which is twice as many products you have shipped for any other months. If you simply divide the number of returns by the number of products shipped … then you will have a fantastic failure rate for this month. This is because all the failures are from previous shipments. And you are comparing this figure to a massive increase in units shipped out this month. This might give you a great failure rate metric for this month – but it is a mirage. It tells you nothing about the life of your product.
- And you need to know why things are failing. Particularly if you have dead on arrival (DOA) or infant mortality failures. Because these are failures you can do something with. You can look at your manufacturing processes or packaging for transportation. Is it a single batch (for example)?
- So how long will it take you to see something going wrong? Think about it. If there is an issue with your products. How long will it take for your failure rate metric to identify a problem? Will this signal be potentially hidden by bad metrics? … where simply increasing the volume of shipments means you see no problem? How much will this cost you when it does become an issue?
Enjoy an episode of Speaking of Reliability. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.
SOR 542 Setting Up to Report Monthly Failure RatesChristopher JacksonshareSocial:Link:Embed:" readonly />https://episodes.reliability.fm/sor/sor-542-setting-up-to-report-monthy-failure-rates.mp3Download Audio RSSShow Notes0 min - History of Reliability Part 3History of Reliability Part 3Abstract
Chris and Fred continue the discussion on the history of reliability engineering. The discussion started with Chris and Adam (you can click here to listen to it) and kept going with Chris and Carl (and you can click here to listen to it). Between all of them, they came up with 8 reliability engineering epochs. Now it is Fred’s turn to work out what has been missed, and what all of this means what reliability engineering looks like in the future.
Key PointsJoin Chris and Fred as they discuss the craftsmen period
Topics include:
- What did Fred think was missing? The use of reliability engineering statistical tools is getting worse and not better … even though we have more tools to do it. Fred pointed out in Chris’s recent webinar on probability plotting (click here if you are interested more!) that some of the attendees probably didn’t even know we could do this sort of stuff by hand. While people in the 1960s and 1970s were doing all these things on paper – they were learning about the underlying statistical process. But with today’s software tools you can put data in and get an answer. But the cost of doing this is not knowing what the process means.
- Is this an epoch in its own right? Maybe this could be referred to as a dark age? But it is a real thing. Today’s academic papers and conferences are not illuminating or useful anymore. Compare this to Wallodi Weibull’s original 1952 paper which is very important, but very simple. The writing style is something we don’t see anymore.
- And how is this affecting us today? We are still using basic approaches and techniques that were developed in the 1950s and 1960s – which have inherent limitations because they were developed without computers. But we still use these basic approaches because they are embedded in software. Which means we don’t need to think about the problem to get a number. So we are in a weird place where everyone either uses terribly ancient statistical equations OR we use ridiculously complex models developed by universities with minimal applicability.
- Anything else? Yes. Reliability engineering is tending to lose the ability to talk. Weibull’s paper is very simple – but the way we present to each other and our organizations involves a lot of jargon and academic arguments for other academics. Does this mean we are losing relevance? Which means we must re-gain the ability to understand our audience. Perhaps.
- Anything else #2? Because there is less talking, we are naturally more guarded. Which means that it is now commonplace to try and avoid even reliability engineers talking about failures. So we don’t admit or talk about failures in tests. And we don’t talk about it between organizations. So as opposed to ‘all ships rising with the tide’ the openness needed for the entire industry to eradicate entire families of failures is no longer a thing.
Enjoy an episode of Speaking of Reliability. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.
Download Audio RSSShow NotesThe post SOR 541 History of Reliability Part 3 appeared first on Accendo Reliability.
0 min - History of Reliability Part 2History of Reliability Part 2Abstract
Chris and Carl continue the discussion on the history of reliability engineering. The discussion that started with Chris and Adam (you can click here to listen to it). In the short time they had to talk about it, they came up with 6 reliability engineering epochs. Now Carl is going to see if there is anything to add and importantly anything to learn.
Key PointsJoin Chris and Carl continue a discussion on the history of reliability. Or more correctly – reliability engineering. Chris and Adam came up with 6 reliability engineering epochs: over-engineering; rapid technological change (World War I); formalizing reliability engineering as a discipline (World War II); the Japanese Economic Miracle; western consumers demanding more; and the computing power of the 1980s and 1990s. What can Carl add to this discussion?
It turns out a fair bit. So we have replaced our last epoch (which was admittedly fairly broad) and replaced it with the following really useful additions to our history.
- New Epoch #6 1980s and Test and Fix or Build-Test-Fix. This happened a lot in the 1980s with more complex machinery and systems being manufactured. Even though computing power was increasing, there was a slow uptake of its potential. So instead many designs focused on building prototypes, trying to see if they worked, and then redesign the next prototype. Without trying to identify potential failures from a scientific perspective at the blueprint stage. Which leads to long and expensive production lifecycles.
- Epoch #7 1990s the Vital Few' and Design for Reliability – Understanding the Physics of Failure (PoF). Market pressures always drive change. Developing products faster and for shorter service lives meant we needed to have a better understanding of the vital few failure modes that really matter. There are typically only a couple of failure modes that drive failure which is great! Using a scientific approach to work out which are the weak points of your design gave manufacturers a key advantage over competitors who were slower to evolve. So this is where things like Failure Mode and Effect Analysis (FMEAs) started to become really powerful.
- Epoch #8 Modelling and Using the PoF. Things like fault trees and reliability block diagrams have been around for a while. But they have not really been used as much as they could have. A 1975 study on nuclear reactors was perhaps the first attempt to do this but it wasn't commonplace. So using reliability modelling started to become more common because it drove design effort in a more targeted way. But there was a catch a thing called reliability prediction started to happen. Tables and handbooks of historical estimates' for reliabilities of different types (like MIL-STD 217) of components started to be used to get reliability models. But these offered little value how could they? Using tables of generic reliability estimates means that a reliable Toyota has the same predicted reliability as a Yugo ( Google that if you haven't heard of it).
What are your thoughts?
Enjoy an episode of Speaking of Reliability. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.
Download Audio RSSShow NotesThe post SOR 540 History of Reliability Part 2 appeared first on Accendo Reliability.
0 min - History of Reliability Part 1History of Reliability Part 1Abstract
Chris and Adam discuss the history of reliability engineering. Everyone (customer, manufacturer, builder) has different ideas of what reliability is. And this has changed throughout history. Perhaps we can learn something from what reliability engineering has also changed throughout history. As they say – those who don’t learn from history are destined to repeat it. This is the first of three podcasts that look at the history of reliability for this purpose: seeing what we can learn to help reliability engineering now and tomorrow.
Key PointsJoin Chris and Adam as they discuss the history of reliability. Or more correctly – reliability engineering. Human beings make things that do what they are supposed to do for as long as we want them to. The way we have approached making things that work well over time has clearly changed over history. So let’s delve a little deeper to see if we can characterize different eras or epochs of reliability engineering and if there is anything we can learn from them.
When Chris and Adam talked about this, they come up with some ideas for different reliability engineering ‘epochs:’
- Epoch #1 – Over-engineering. Today, we are lucky to have access to a wealth of understanding of how things fail from a very scientific perspective. But this was not always the case. Cave-men and cave-women needed to construct stone axes that would last – but couldn’t do extensive testing on those axes in a laboratory. So they had to use their judgment to make strong axes by making them very, very robust. And this didn’t change for a very long time. There are machines, tools and buildings from the 1800s that work really, really well today (providing they were maintained). And they were all very big, heavy and robust. There is a reason we say they don’t make them like this anymore.
- Epoch #2 – World War I. World War I was really the first time where generational technological change started to happen more frequently than human generational change. Aircraft, weaponry, tank and explosive technologies were being developed so fast that what was once state of the art would very quickly become outdated and overmatched. So for the first time, the idea of not having to make tanks and other machines that you could one day give to your child meant we could make more of them (and get them much faster). But things sort of got stuck here for a bit … mainly due to the Great Depression.
- Epoch #3 – World War II. Technological change became faster and faster. Things like electronics became more important. And the thing about electronics is that you can’t see deterioration they way you can observe corrosion and cracking. So reliability engineering became formalized as its own discipline. Training and educational institutions started to offer reliability engineering-specific courses and lessons. And to some, this was the birth of reliability engineering as we know it.
- Epoch #4 – The Japanese Economic Miracle. There are several geopolitical factors that dominated how Japan emerged from World War II. But perhaps the most important element was that it became a technocratic society. With foreign funding and a blue sky cultural rebuild project, the best leaders (not the most popular or most connected people) rose to the fore and focused on turning Japan into a manufacturing power-house. Japanese manufacturing before World War II was notoriously poor quality. Not anymore. They focused on things that matter. They worked out how to make high-quality products. And they worked out how to embed this culturally. And it could be argued the rest of the world still hasn’t caught up. Think the Toyota Production System.
- Epoch #5 – The 1970s and customers wanting more. The 1970s oil crisis meant that western consumers started focusing on things like fuel economy for cars and product costs in a way that they never previously had to. Money was tight. And key supplies were rationed. So they had to do more with less. And with the emergence of Japanese vehicles into western markets … they realized they could start demanding more.
- Epoch #6 – 1980s and 1990s and computers. Now we could start solving some of the more complex reliability engineering equations and challenges. This allowed us to do some more sophisticated analysis – but it also took some of us away from focusing on good design principles. Has this been an overall good thing?
And what about the future? Perhaps we could anticipate …
- … an emergence of a new reliability engineering culture where businesses and other organizations do away with useless analysis and calculations and start linking performance (both product and human) to strategic objectives in a way that everyone gets and can buy into.
- … reliability of services such as product delivery, data provision and so on that sees reliability engineering stop being as focused on individual products or machines and more on the ultimate ‘success’ of a team of machines, humans, computers and mother nature!
- … big data that is useful and less of the buzzword it tends to be today.
What are your thoughts?
Enjoy an episode of Speaking of Reliability. Where you can join friends as they discuss reliability topics. Join us as we discuss topics ranging from design for reliability techniques to field data analysis approaches.
Download Audio RSSShow NotesThe post SOR 539 History of Reliability Part 1 appeared first on Accendo Reliability.
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