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

Professional Societies: The Rules Have Changed Abstract Greg and Fred discussing how The Rules Have Changed for Professional Societies as well as for most of us. Key Points Join Greg and Fred as they discuss the role of professional societies such as IEEE, ASME, ASQ, and others in the age of social media and fast information. Topics include: What is the role of the professional society for guiding the future of the profession as well as its body of knowledge. Why are professional societies reactive instead of proactive in developing new ideas and products. What can professional societies do to set the agenda for the profession. 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 Related Topics How to Attend a Reliability Conference (Opens article in a new browser tab)   The post SOR 814 Professional Societies: The Rules Have Changed appeared first on Accendo Reliability.

Quality of Decisions Abstract Greg and Fred discussing how people make important decisions and why decision quality is important. Key Points Join Greg and Fred as they discuss Topics include: Why is decision making in reliability important. How to use reliability tools for effective decision making. What are the critical steps in Fred’s new book on reliable decision making. Why the process of decision making may be more important than the result. 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 Related Topics   Risk Decision Making, Frameworks, and Assessments(Opens podcast in a new browser tab) SOR 875 What Should a Reliability Engineer Do(Opens podcast in a new browser tab) The post SOR 813 Quality of Decisions appeared first on Accendo Reliability.

Storage of Test Parts Abstract Dianna and Fred discussing the effects of handling, cumulative test, and storage of test parts on test results. Key Points Join Dianna and Fred as they discuss experiences of when testing product went awry because of handling, cumulative test, and storage of test parts. Topics include: identifying the true failure mechanism keeping in mind the things we don’t specify or control for test can affect results being present to identify “hidden” stressors Listen-in to get ideas of what you might be missing in your test plan. 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 812 Storage of Test PartsDianna Deeneyshare Social: Link: Embed: https://episodes.reliability.fm/sor/sor-812-storage-of-test-parts.mp3 Download Audio RSS Show Notes Corrosion takes time. If it's not a mechanism that we're actively testing for, it can still show up as a failure mechanism because of how or how long the parts are stored. Storage itself can be a stressor. For example, for accelerated tests involving temperature and humidity: even if parts are pulled over the weekend, they're still being exposed to cycling because of their storage. Handling matters. Ask about and watch how parts are moved from test to test to understand what extra stressors may be added to your test plan. What to do: Think through every step of the test process, including handling, storage, and transportation of parts between tests. Ensure we're defining failures and finding failure mechanisms (e.g. not blaming a corrosion issue on a high temperature issue). Related Topics SOR 796 Very Long Term Storage Question(Opens podcast in a new browser tab)

Reliability Prediction Standards Abstract Dianna and Fred discussing the history and application of published parts count prediction models and standards in reliability analysis. Key Points Join Dianna and Fred as they discuss the history of the parts count prediction models that are published for sale or that used to be publicly available but have since been withdrawn. Topics include: A story of how these standards were created Why it and similar standards are out of date Why some people still ask for it What to do instead 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 Published parts count prediction models: please don't use these. These models are not useful, and they are misused. Some of the reasons these models are out of date: They’re simply not maintained. Data collection is a challenge. Companies do not share their information. Companies are competing for best products. Standards lump all products together. Companies are concerned about litigation and do not want to publish the reliability information of their products. Data listed in the standard are not a reflection of field reliability. People may still request the parts count reliability because of holdovers on procurement forms. If the calculation is not going to be used to determine any kind of reliability information, then we can provide it. Otherwise, don't use part count prediction models just because it's simple to do.   Field reliability depends on your parts, your designs, and your customers. Users need to maintain and update these reliability models, otherwise they become irrelevant. It's difficult to find really good TTF (time to failure) data at the component level. From vendor-to-vendor we see widely different claims. And companies are reluctant to share information because of trade secrets. Some companies perform reliability testing on their components. They may report it as tests of the weakest component in their system. If it's important for your designs: Create a block diagram. Try to get the distributions NOT failure rates, FIT Rate, or MTBF. Today's software is powerful enough to be able to use block diagrams with reliability distributions. Ask Vendors: What's the TTF distribution and how do you know, and what's the failure mechanism? Or partner with vendors to test critical components. There are many mutually beneficial ways to work with vendors so you can get the reliability data you need. Related Topics SOR 069 Should reliability prediction be part of your reliability plan?(Opens podcast in a new browser tab) The post SOR 811 Reliability Prediction Standards appeared first on Accendo Reliability.

Metrics and Games Abstract Carl and Fred discussing a listener question on maintenance strategies, and a company mandate metric comparing preventive and corrective maintenance tasks. Key Points Join Carl and Fred as they discuss how metrics can become a numbers game if they are used incorrectly. Topics include: Sometimes a metric can alter behavior in the wrong way if people learn to “game” the system. How metrics can become a numbers game, especially if too much force is used to meet a threshold. Using RPN thresholds, as an example Ratio of corrective to preventive tasks is vulnerable to numbers game. Ask: what you are really looking for? How do we achieve that? The *quality* of corrective and preventive tasks is essential. RCM can be used to get the right tasks; needs the right inputs and criticalities. How do you encourage more preventive maintenance in a meaningful way. What are quality objectives for an RCM project? How can these be used? What are quality objectives in an FMEA project and how are they used? Trusting the team vs monitoring data What is role of Root Cause Analysis in this discussion? What can you do to improve maintenance procedures when in middle of production? Effectiveness of corrective actions How to implement future preventative actions Use of 80/20 rule in prioritizing tasks 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 Related Topics Corrective Action Question(Opens article in a new browser tab) The post SOR 810 Metrics and Games appeared first on Accendo Reliability.

The Value of Curiosity Abstract Carl and Fred discussing what brings enjoyment to one’s life and work, and how to explore and learn, with curiosity. Key Points Join Carl and Fred as they discuss the value of curiosity in our day-to-day work. Topics include: Using what we know in science and engineering to understand problems and explore creative solutions. Curiosity breeds energy and passion, and is contagious. Aligning your skills with your passions and filling a need. Use the 5 whys; always ask “why”? Questions explore things we don’t know. Don’t let curiosity be driven from your mindset. Explore inside-out thinking and balance with outside-in thinking. Keep your mind open to how things fail. 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 Related Topics 11 Motivations to Learn Reliability Engineering(Opens article in a new browser tab) The post SOR 809 The Value of Curiosity appeared first on Accendo Reliability.

What is a Reliability Score? Abstract Chris and Fred discuss how we communicate reliability to our customers. And they haven’t completed university courses in reliability engineering … Key Points Join Chris and Fred as they discuss the prevalence of reliability scores when it comes to communicating reliability. We often have ‘star ratings’ or ‘reliability scores out of 100.’ These are metrics that are intended to simplify the reliability performance of things like printers through to personal motor vehicles. Topics include: What are we talking about? Organizations like JD Power come up with ‘reliability scores’ for new cars. When you scratch the surface, you see that these scores are based on customer feedback for the first four years of its life, and other scores based on how many ‘problems’ vehicles experience in that period. But what does this say about how long the drive train is going to last … noting we expect many drive trains to last for decades in certain use scenarios? Manufacturing is important. There are plenty of examples where (typically Japanese) manufacturers create high-quality parts that are well ‘centered’ within specification limits are more reliable than other ‘in-specification’ components that are ‘close’ to specified limits. What about technology? The VW beetle is an incredibly simple air-cooled engine that is not as efficient as other engines … but incredibly reliable. Electric vehicles don’t involve transmissions, combustion, and lots of other things that are inherently challenging to keep reliable. So technology plays a very important role in reliability. How is this scored? So how else do we ‘gauge’ reliability? 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 Related Topics Scoring Your RCM Effort(Opens article in a new browser tab) The post SOR 808 What is a Reliability Score? appeared first on Accendo Reliability.

Confidence and Tolerance Intervals Abstract Chris and Fred discuss the difference between ‘confidence,’ ‘tolerance’ and ‘prediction’ intervals. Is there any point in understanding the difference between these concepts? … or is it something only statisticians find useful? Key Points Join Chris and Fred as they discuss the difference between ‘confidence,’ ‘tolerance’ and ‘prediction’ intervals. Reliability, quality, and manufacturing engineering involve lots of different statistical concepts. So do these concepts help us? Topics include: Tolerance Intervals. Take for example the process of baking bread. Baking bread is a random process. If you are good at baking bread, each loaf should be relatively similar to every other loaf. But there will be some variation from loaf to loaf. This is what makes it random. One characteristic of bread is ‘chewability.’ It is measured in terms of force (Newtons). So if we were to look a 1000 loaves of bread we baked on a particular day, the 95 % tolerance interval of bread chewability will be that interval within which 95 % of our loaves of bread fall. So for example, if 95 % of our loaves of bread have a chewability that is between 6.871 and 7.249 Newtons, then the 95 % tolerance interval (for chewability) is 6.871 to 7.249 Newtons. Confidence Intervals. Tolerance intervals are characteristics of bread. Confidence is a measure of you. If we keep looking at our bread, we might be interested in a particular random process characteristic. Like the mean or average chewability. Let’s say that we measure the chewability of one loaf of bread, and it turns out to be 6.945 Newtons. We can use this figure to estimate the mean chewability of each loaf of bread. But how accurate is this estimate? How certain can we be that the mean of every loaf of bread is close to the chewability of a single loaf of bread we measure (6.945 Newtons)? The answer is … not very confident. So if we measure more loaves of bread, and increase the amount of data we have, then we can estimate the mean with increasing accuracy. We can use statistics to actually capture or describe this confidence interval. So the 95% confidence interval on chewability mean will be much wider if we have only measured one loaf of bread. Prediction Intervals. This is much like the tolerance interval, but instead it applies to something that is ‘yet to happen.’ We might (for example) be able to calculate the tolerance interval for the 1000 loaves of bread we baked today, and then say (with some justification) that we would expect the same thing to happen tomorrow. There are some circumstances where we might want to do things like change baking temperature or the amount of flour we use, which means that we might be able to calculate the effect this has on the chewability of our loaves of bread tomorrow. So they are not always the same thing. One more thing about confidence intervals. Tolerance and prediction intervals technically do not change based on how many samples we have investigated. Confidence does. The more data we have, the more confidence we have. Tolerance intervals (for example) are ‘what they are.’ We just need to get enough data to find them! Do these definitions help you? Great! Use them. If not … don’t use 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 Related Topics Reliability Techniques For Analyzing And Improving Fault Toleranc(Opens article in a new browser tab) The post SOR 807 Confidence and Tolerance Intervals appeared first on Accendo Reliability.

MEOST Setup Remotely Abstract Kirk and Fred discussing Multiple Environmental Over Stress Test or MEOST. Key Points Join Kirk and Fred as they discuss the term MEOST and how it is very similar to HALT in the use of stress to find latent defects or weaknesses. Topics include: Gregg Hobbs was very possessive of the term HALT which he had coined for his strength limit testing, so many organizations use other acronyms to describe HALT. Fred’s favorite stress in HALT or MEOST is vibration on mounted components especially the ones that can move relative to each other. That condition often leads to reliability issues and is why vibration HALT is so useful for Power supplies. Trying to conduct or direct at HALT or MEOST in remote labs is extremely difficult if not impossible to do if the lab does not have a thorough understanding of HALT and the goals of HALT since most companies will not increase margins beyond stress specifications. The second question is about testing for a photo diode reliability issue. There are so many possibilities of the cause, a deep failure analysis and measurements need to be made before determining the stresses needed to screen the units. 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 You can now purchase the recent recording of Kirk Gray’s Hobbs Engineering 8 (two 4 hour sessions) hour Webinar “Rapid and Robust Reliability Development 2022 HALT & HASS Methodologies Online Seminar” from this link. 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 – 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. Related Topics Eliminating early life failures(Opens article in a new browser tab) The post SOR 806 MEOST Setup Remotely appeared first on Accendo Reliability.

Reliability Spooky Stories Abstract Kirk and Fred discussing  and reflecting on some of the spooky reliability problems we have seen (or not seen) that sometimes have haunted us on this  Halloween 2022 episode of SOR Key Points Join Kirk and Fred as they discuss Topics include: Fred recalls a meeting that many engineers shared scary gremlins and bugs that get into our designs, including large rats that chew on insulation in the middle of the night. We know that many creatures, snakes and spiders and squirrels are many times the cause of power systems shorting or catching fire. Fred conveys a study and testing of fire ants being attracted to weak electromagnetic fields and labs that have fire ant resistance testing. Kirk discusses how working on high vacuum semiconductor manufacturing equipment exposed him to some scary invisible dangers such as X rays from Ion Implanters. A company that made small Voltage Controlled Oscillators (VCO) had a damaged varactor diode that was causing field failures. The president of the company believed that these diodes where damaged on a day there was a lightning storm and the voltage spike traveled through the building and sensitive instruments to the test rig at the exact time of the test (15 seconds) and destroyed this one component in each of 30 or more as each units was tested for 15 seconds. That is quite a synchronized lighting storm  Spooky crazy theory. 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 You can now purchase the recent recording of Kirk Gray’s Hobbs Engineering 8 (two 4 hour sessions) hour Webinar “Rapid and Robust Reliability Development 2022 HALT & HASS Methodologies Online Seminar” from this link. 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 – 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. Related Topics When Rules are Made to be Broken!(Opens article in a new browser tab) The post SOR 805 Reliability Spooky Stories appeared first on Accendo Reliability.