Speaking Of Reliability: Friends Discussing Reliability Engineering Topics | Warranty | Plant Maintenance

Hints to Have a Proactive Reliability Program Abstract Chris and Fred discuss ‘proactive’ reliability engineering … and trying to get out of being ‘reactive.’ Some entire organizations are structure around waiting for the catastrophe to happen before we fix it. So changing perspectives can be challenging. Key Points Join Chris and Fred as they discuss what ‘proactive’ reliability engineering is, what it means, and why you should love it. Topics include: Getting out of the ‘reactive’ quagmire. Many organizations are structured to be nothing but reactive. So even though they might ‘intuitively get’ that they need to become more proactive (because they are constantly fighting fires), they culturally struggle to make the switch. One of the tricks is to focus on the immediate and personal benefits of reliability engineering. Reliability engineering starts resolving problems TODAY. Trying to convince employees that they should ‘do’ reliability engineering because of ‘brand reputation’ and ‘customer expectation’ is really difficult. This is impersonal and seems to benefit the organization … not the engineer who wants a positive performance appraisal this year. Urgent versus important. Responding to a customer who has a problem today is ‘urgent.’ We like solving ‘urgent’ problems which are immediate and create a checklist we get a great deal of satisfaction from ticking off. But this might not be ‘important.’ An ‘important’ issue is (for example) not having a culture, organizational structure and set of resources to have a proactive approach to reliability. ‘Important’ issues are often bigger, longer, and perhaps involve more uncertainty. So … they often get shelved in preference for ‘urgent’ issues. What can we do to become proactive? Make reliability RELEVANT. For example, create a reliability value map that ties reliability performance metrics (whatever they are for your organization) to VALUE. How much does downtime/missed shipping/warranty action/production delays/et cetera cost. Understanding this means we start understanding why we do specific reliability activities. … and then, communicate! Align intents, have a singular focus on how much value we lose when things go wrong, and start the conversation. Leaders cannot (of themselves) make this happen. You need the smart people that work in your organization to become proactive on their own. By definition … you can’t be proactive for them. 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  RSS Show Notes   The post SOR 655 Hints to Have a Proactive Reliability Program appeared first on Accendo Reliability.

Reliability Starts at the Top Abstract Chris and Fred discuss how reliability starts at the top of every organization. And by that, we mean … leadership. What does that mean? How can the CEO be more important for reliability performance than the reliability engineer with decades of experience and post-graduate qualifications? Key Points Join Chris and Fred as they discuss how leadership drives reliability. From the top. Topics include: Chris says ‘starts at the top.’ Fred says ‘supported by the top.’ Fred pointed out that a lot of good ideas come from the bottom. And in that way, reliability might not start from the top. Chris doesn’t challenge that, but he thinks that it is the leadership team that start by creating the culture that empowers, enables and encourages employees to come up with great new ideas. What do you think? Boeing is a great example of this. Boeing’s leadership team changed strategies a few years ago. They pushed suppliers to drive down costs (and if they didn’t, they were blacklisted). They tried to guarantee access to the market by launching (ultimately futile) legal action against competitors to try and control access to the North American market. They tried to short-circuit regulatory certification. They started to move away from focusing on great aircraft design. And the investors loved it! Profit went up because costs were cut. But a price had to be paid eventually … and that happened when 737 Max 8 aircraft crashed. You can cost cut yourself right out of business. And engineers often know. Boeing, NASA and lots of other organizations have had engineers warn leadership teams about impending failures. When ‘leadership’ goes against, sound engineering advice, physics rules. It starts at the top. But it needs to go all the way down. One of the most important parts of leadership is to ensure that subordinate leaders are also good leaders. Otherwise, things just stop. And in many cases, leaders can say they value reliability as much as they want, but if they wander into a vendor meeting demanding that they cut costs and do everything faster … then reliability has effectively stopped. 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  RSS Show Notes   The post SOR 654 Reliability Starts at the Top appeared first on Accendo Reliability.

More Than One Root Cause Abstract Carl and Fred discussing the subject of root cause. How many “root causes” can there be? Is there only one “root cause” for a problem? What about events or conditions that happen in tandem? Key Points Join Carl and Fred as they discuss how many events or conditions can contribute to problems, and whether there can be more than one “root cause.” Topics include: Independent vs tandem causes Sequential vs parallel events Technical vs business processes Digging deeper to get to root cause; five whys Business FMEA What about interfaces? 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  RSS Show Notes   The post SOR 653 More Than One Root Cause appeared first on Accendo Reliability.

Reliability and Risk Management Abstract Carl and Fred discussing the relationship of reliability and risk management, including areas of overlap and linkages. Key Points Join Carl and Fred as they discuss the body of knowledge of reliability and how it relates to risk management. Definition of “risk” Technical risk vs business risk Preparation can reduce uncertainty risk Severity and probability of harm, as elements of risk Role of Hazard Analysis Risk as superset of reliability, availability, maintainability Systematic process to assess risk FMEA, FTA, and risk management Output of FMEA: risk reduced to acceptable level What is acceptable risk? 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  RSS Show Notes   The post SOR 652 Reliability and Risk Management appeared first on Accendo Reliability.

Suspected or Known Problem Abstract Kirk and Fred discussing the challenge of finding a latent problem in a product after your company has been producing and selling for some time. Key Points Join Kirk and Fred as they discuss dealing with a latent reliability problem that may exist in a certain percentage of the product shipped and in use. Topics include: Today the internet and social media can a should be monitored for feedback from customers and failure reports, especially for low cost products that often will be tossed in the trash instead of returned. Safety issues are usually addressed quickly by the manufacturer, as the potential liability costs can be significant. What can a company can do once a field problem is discovered through customer feedback on failures that may be reported through websites. 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  RSS Show Notes Please click on this link to access a relatively new analysis of traditional reliability prediction methods article from the US ARMY and CALCE titled  “Reliability Prediction – A Continued Reliance on a Misleading Approach” For more information on the newest discovery testing methodology here is a link to the book “Next Generation HALT and HASS: Robust design of Electronics and Systems” written by Kirk Gray and John Paschkewitz. The post SOR 651 Suspected or Known Problem appeared first on Accendo Reliability.

Reliability Expectations Abstract Kirk and Fred discussing how we continue to evolve our reliability expectations  as technology becomes more robust and reliable. Key Points Join Kirk and Fred as they discuss the progress of expectations of reliability in cars, and electronics, have become more reliable. Topics include: Sensors, like tire pressure monitors on each tire and other monitoring systems have help prevent many catastrophic failures such as flat tires. Technology moves on and technological obsolescence  has left behind many products that still have plenty of life left in them. Engineers still always have to make tradeoffs in how much we can make a product more robust and still keep it competitively priced. 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  RSS Show Notes Please click on this link to access a relatively new analysis of traditional reliability prediction methods article from the US ARMY and CALCE titled  “Reliability Prediction – A Continued Reliance on a Misleading Approach” For more information on the newest discovery testing methodology here is a link to the book “Next Generation HALT and HASS: Robust design of Electronics and Systems” written by Kirk Gray and John Paschkewitz. The post SOR 650 Reliability Expectations appeared first on Accendo Reliability.

Extrapolation and Sample Sizes Abstract Chris and Fred discuss (essentially) how many ‘things’ you need to see to know enough about those ‘things.’ We see this conundrum across all sorts of fields of study. How many kangaroos do I need to capture and weigh to get a good understanding of the entire population’s typical weight? Delete kangaroo and insert whatever thing matters to you. Key Points Join Chris and Fred as they discuss how many samples we need to take from a population we need to take to have a good understanding of the typical nature of the population you are studying. Topics include: Let’s talk about information. Data contains information. You can extract information from data through data analysis. And if data comes from a random process (like failure), then each new data point adds more information to your understanding of what is happening. So let’s say we are measuring dimensions of molded parts being produced by a manufacturer. If the first molded part we measure is within tolerances … are we confident that the rest of the molded parts are also within specification? Are we more confident if the second part we measure is also within tolerances? Yes … but perhaps not by much. How many more parts do we need to measure … with all of them being within tolerances … for us to be confident enough that all the molded parts are within tolerances? Models are information. We know about things like bell curves. If we assume that (for instance) a bell curve represents our process, we need less data when it comes to data analysis. Why? Because a model contains information. Models can also be misinformation. Let’s just say that you are manufacturing a molded part. Your process is so good and so refined, that the dimensions of each part are so far within tolerances that they don’t even think about being ‘out of spec.’ EXCEPT … when the manufacturing process recalibrates flow rates. The first five to ten molded parts that are made during recalibration have dimensions that are often skewed outside of tolerances. In this scenario, there are two processes – (1) steady-state and (2) recalibration. These two processes are described by different models. If you find a model that best fits ‘steady-state’ data, you really can’t say anything about the nature of part dimensions during recalibration. So how well do you know your process? … and extreme values? Depending on your source, the average height of a human male is 70 inches. Again, depending on your source, the standard deviation of the height of a human male is 4 inches. We also see that the bell curve we mentioned above seems to do a pretty good job of modeling human height. The problem is that the bell curve that fits the data also suggests there is a finite chance that someone can be zero inches (or shorter!) Many models can do a great job of modeling the majority of data. But they are often not very good at modeling extreme cases. And in reliability engineering, we are often interested in extreme cases. Such as when 1 %, 0.1 %, or 0.001% of our things failing. 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 Show Notes   The post SOR 649 Extrapolation and Sample Sizes appeared first on Accendo Reliability.

Accelerated Testing Assumptions Abstract Chris and Fred discuss accelerated testing. Accelerated testing is great for getting lots of information in a short period of time. You can compress a lot of ‘real-time’ life into a really small amount of testing. But how do you do it right? You need to understand the underlying physics of failure to work out how the compression of time works. Key Points Join Chris and Fred as they discuss accelerated testing. Fred once had a client, who was in the process of doing accelerated testing, tell him that they were going to assume that the thing they were studying had this thing called ‘activation energy.’ This relates to a model that helps us understand the rate at which a chemical reaction occurs. The higher the activation energy, the slower the chemical reaction occurs. Temperature (thermal energy) often drives chemical reactions because there is more energy to meet the ‘activation energy’ requirement for the reaction to occur. So all we need to do is turn up the temperature to make things happen faster? But … Fred’s client simply assumed that the activation energy for the particular chemical reaction was 0.7 (the units are omitted for the gist of this podcast). This is not the way to do this … Topics include: Reach out to an expert. If you need to make an assumption about how your thing degrades, ask an expert. There are plenty out there. We don’t always have time to run tests to get this information ourselves. So get it from someone else! If you can’t find an expert, go to the library. What is your model? You have to have a model for accelerated testing. This model allows you to create what we call acceleration factors (AFs). If you have an AF of 10, that means every 1 hour of testing (perhaps at higher temperatures) equates to 10 hours of ‘real-life’ use. To be able to quantify your reliability estimates, these AFs need to be accurate. How accurate is your AF if you assume that the activation energy is 0.7 without any further thought? Accelerated testing factors are RARELY independent. Fred’s client not only wanted to increase temperature – they also wanted to increase the load (pressure). The huge problem with this is that these factors are rarely independent. That means that if we increase the load we are also likely to change the way temperature increases the rate of chemical reaction. And all sorts of other things can happen as well. Sometimes increasing pressure changes the ‘state’ of the thing you are studying. The molecular structure changes, meaning that other accelerated testing models become irrelevant. It is very challenging to have more than one factor applied to accelerated testing. Are you trying measure or improve reliability? Accelerated testing can be hard. But if you are only interested in improving reliability, then you can move into the domain of highly accelerated life testing (HALT). This is where stresses are increased in a scientific way, but not in a way where we try to extrapolate reliability in ‘real-life’ conditions. HALT focuses on finding the weak points only. So what are you trying to achieve? 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  RSS Show Notes   The post SOR 648 Accelerated Testing Assumptions appeared first on Accendo Reliability.

Deterministic versus Probabilistic Abstract Chris and Fred discuss what it means to be ‘deterministic’ versus ‘probabilistic’ … and what that means for reliability engineering. Know what these words mean and want to learn more? Don’t know what these words mean and want to understand how they could help reliability engineering? Listen to this podcast. Key Points Join Chris and Fred as they discuss what it means for us reliability engineers to think ‘deterministically’ versus ‘probabilistically.’ Topics include: Determinism means that everything has a cause and all outcomes can be completely defined (i.e. predicted) based on what has happened beforehand. There is no uncertainty, and hence no variation in what we observe. Probability describes the idea that for the same set of inputs or events, we can different outcomes … or variation in results. Two things can be true. Everything is deterministic. Everything happens for a reason. But we often have no hope of measuring all inputs. Think of fatigue cracking. We are pretty good at understanding how fatigue cracks propagate through steel. But to know exactly when a strut will fail due to fatigue, we need to know the precise location of every atom, every impurity, every surface crack, the mass of every car driving over that bridge and so on. We can’t ever do this. So we can combine deterministic models of fatigue cracking with probabilistic models to capture the uncertainty in the inputs to come up with something really useful. It all comes down to the decision you need to make. If you want to improve reliability, you need to know why your thing is going fail. Which means you need to have a deterministic model of why things fail. If you want to understand when your thing is likely to fail, you need a probabilistic model. Or a combination thereof. So what decision are you trying to make? 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  RSS Show Notes   The post SOR 647 Deterministic versus Probabilistic appeared first on Accendo Reliability.

The Hunt for Reliability Training Abstract Chris and Fred discuss how you go about ‘hunting’ reliability training. And we do mean ‘hunt.’ Key Points Join Chris and Fred as they discuss how you go about getting good training for your organization. You can’t simply go with the first result that pops up in a Google search. And you also can’t go with the same ‘guy’ you have always gone with if you don’t know why. So where do you start? What are you trying to achieve? Why are you doing it? Before you go looking for training, work out what problem you are trying to solve. If you don’t know the problem you need to solve, then you don’t know what ‘success’ looks like. If you don’t know what ‘success’ looks like, then you don’t know if a particular training course is going to help. It could be that you need to train people to use your Highly Accelerated Life Testing (HALT) chamber. It could be that you want to start a reliability conversation in the organization, and you need people to be more generally aware of reliability topics. Understand what you want and then go and get it. It is OK to get taught more than you need to know. But not too much. One of the many complaints about high school and university courses is that they teach you mathematics and other stuff that you ‘never’ use in the real world. This can be technically true, but practically false. Depending on where you are now, you might never use the differential calculus you studied in the 10th – 12th grades. But … this learning how to do calculus did exercise your brain. It made you smarter. It made you better. But there is obviously a point where endless statistics is not useful for drafting a reliability plan. Is training the right path anyway? Let’s say that your organization wants to roll out a new program. A new initiative. A new way of doing things. Is bringing in outside training experts the best way of making this happen? Or would it perhaps be the leadership group making the case, explaining why the new ‘thing’ is important, and how you will be valued as part of it? Training might be an important part of the second option … but training should never be the simple answer to a more encompassing problem. Perhaps you could start with reading a book. Or Googling. What are you trying to achieve? ‘Virtual’ versus ‘in-person?’ It wasn’t that long ago that ‘virtual’ or ‘online’ training was a poor cousin to ‘in-person’ training. That has since changed. Some virtual training allows all sorts of useful animations and visual aids … for teachers willing to go the extra mile. So while ‘in-person’ training certainly has its own pros and cons, it sometimes can’t provide all the advantages of ‘virtual’ or ‘online’ training. What will work for you? 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  RSS Show Notes   The post SOR 646 The Hunt for Reliability Training appeared first on Accendo Reliability.