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

Ten Career Gems for New Reliability Engineers Abstract Carl and Fred discuss our top advice for those starting a role as a reliability engineer for the first time. Key Points Join Carl and Fred as they discuss Topics include: Academic question: What do you do when you research a subject and there are no meaningful results, and nothing to publish? By what criteria should you select future projects? Academic question: Feel like missing something in education program, how to get out and actually apply reliability? There are many potential paths in a reliability career What should you do when you finish reliability educational program? What are the opportunities? Advice to new graduates or new reliability engineers: 1. Listen to successful people in your field and your company; 2. Connect with customers who actually use your product; 3. Find your network and your partners, including in marketing and finance; 4. Do a really good job where you are for minimum two years; 5. Get involved in professional organizations; 6. Don’t be afraid to talk with management; 7. Augment tech skills with soft skills (reference chapter 11 and 12 of The Process of Reliability Engineering; ; 8. Speak up if something is not going the right way (but do your research first); 9. Ask questions, be curious, learn; 10. Continue learning with new courses and self study. 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 1089 10 Gems Career Start Advice appeared first on Accendo Reliability.

AI Future of FMEA Abstract Carl and Fred discuss the use of AI with FMEA, what works and what does not work. Key Points Join Carl and Fred as they discuss the broad subject of FMEA and AI. We look at early lessons learned, discuss opportunities, and focus on the most important concerns. Topics include: How FMEA can interact with Model-Based Engineering? FMEA pre-population, which fields can be pre-populated and which should not? What is role of human team in FMEA? What are primary ways to reduce FMEA in-meeting time? How do team-based FMEAs, done very well, compare to AI automated FMEAs? How can AI augment well-done FMEAs? What specific support can AI provide to FMEA? AI can review past problems and provide excellent input to new FMEAs Look for areas of concern by proper FMEA team One concern about pre-population: people don’t see what isn’t there Consider AI bot as FMEA team member, with specifically defined role AI cannot replace human creativity and ingenuity Part of the value of FMEA is the deep discussion between subject matter experts AI will not solve potential blind spots AI can help with augmentation for FMEA, but not taking over the FMEA process. Download Audio RSS Show Notes   The post SOR 1088 AI Future of FMEA appeared first on Accendo Reliability.

What do Reliability Engineers Do? Abstract Dianna and Fred discuss what do Reliability Engineers do? Key Points Join Dianna and Fred as they discuss what do Reliability Engineers do? An RE’s role extends far beyond just crunching numbers and running tests. Topics include: How they act as crucial links between diverse teams Their ability to help teams shape decisions that profoundly affect product performance, customer satisfaction, and business outcomes. Bridging departmental silos, managing inherent conflicts, and advocating for the voice of the customer They also talk about why interpersonal skills and the ability to influence are just as vital as technical expertise for a successful reliability engineering career, even if they aren’t taught in school. 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 In this episode of Speaking of Reliability, Fred Schenkelberg and Dianna Deeney dive into a question: “What does a reliability engineer do?” They quickly establish that while data analysis, regression, and failure analysis are indeed tools they use, these activities do not fully define the job. Fred and Dianna clarify that reliability engineers are fundamentally problem solvers and problem finders, often serving as bridges between different ideas and groups within an organization. They hold an important independent viewpoint and use their tools and data to influence decision-makers, impacting critical aspects like customer satisfaction, product pricing, field longevity, and safety. They emphasize that reliability engineers possess a unique, overarching view of the product due to their extensive collaboration across various departments, including marketing, sales, design, manufacturing, and vendors. This cross-functional engagement allows them to act as advocates for the customer, ensuring the product works reliably in its real-world environment. A key challenge they highlight is the need to prioritize important, preventive work over merely reacting to urgent failures, setting up organizational “guard rails” to systematically prevent problems. They also frequently find themselves managing inter-departmental conflicts arising from differing constraints and perspectives, a role often requiring them to step in and facilitate solutions. Ultimately, Fred and Dianna stress that while a strong technical foundation is essential, the ability to work with and influence people is a crucial, yet often untaught, skill for effective reliability engineering. This interpersonal aspect, combined with their expertise, makes reliability engineering a truly interesting and empowering position within any company. The post SOR 1087 What do Reliability Engineers Do? appeared first on Accendo Reliability.

Enough Data? Abstract Dianna and Fred discuss a common reliability engineering dilemma: do we have enough data? Is data nirvana achievable? Key Points Join Dianna and Fred as they discuss a common reliability engineering dilemma: do we have enough data? Is data nirvana achievable? Topics include: Hidden challenges for RE, from too little to overwhelming amounts Departmental silos and data quality nightmares The art of purposeful collection Buy-in for better data and how explaining the ‘why’ behind its collection can transform resistance into collaboration 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 In this episode of Speaking of Reliability, Fred Schenkelberg and Dianna Deeney tackle a common question for reliability engineers: Do we have enough data to do our job? They discuss the dual challenges of both not having enough, particularly for new and unproven products that require costly testing. On the other hand, we’re sometimes overwhelmed by excessive information without clear direction on its utility. A significant part of their discussion revolves around the accessibility and quality of it. Data often resides in departmental silos (e.g., customer service, finance, manufacturing) that don’t readily share information. They highlight the extensive time spent cleaning up inconsistent, error-prone sources from disparate systems, often finding issues like incorrect data types or format changes. Dianna notes that while information collection falls under management responsibility and quality management systems, reliability engineering often requires advocating for specific needs that might not be captured by standard financial or customer service metrics. They emphasize the importance of foresight and cross-functional collaboration to ensure useful data is collected from the outset, ideally before a product’s market release. This includes identifying critical parameters and coordinating with customer service. Fred shares an insightful anecdote about how poorly designed forms can lead to skewed data, illustrating the need for a “usability engineering” approach even for checklists. They conclude that while obtaining “nirvana” with perfectly trustworthy and available data is rare, explaining the purpose and value of collection can significantly improve buy-in and collaboration across an organization. The post SOR 1086 Enough Data? appeared first on Accendo Reliability.

Risk Monitoring Triggers Abstract Greg and Fred discuss ways to detect and monitor changes in a system.  So, what is the trigger to indicate an event,  threat, or anomaly that can result in a risk.  This becomes critical if you want to focus on the critical few NOT the insignificant many. Key Points Join Greg and Fred as they discuss what triggers risk and how to monitor it.  Topics include: What is a risk trigger? How to monitor significant events, threats, and anomalies. How to be proactive, preventive, predictive, and preemptive. How to separate the critical few from the insignificant many. 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 1085 Risk Monitoring Triggers appeared first on Accendo Reliability.

Reliability Allocation Abstract Enrico and Fred discuss various approaches to allocation. Key Points Join Enrico and Fred as they discuss the pros and cons of different approaches to reliability goal allocation for subsystems and components. Topics include: Is there value in allocation goals for each component in a system? What is the purpose of allocation? How the process of doing the allocation can benefit the focus on improvements that matter. 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 1084 Reliability Allocation appeared first on Accendo Reliability.

Portable Device Feasibility Abstract Chris and Fred discuss how we assess product feasibility … at the concept stage! Great topic. Key Points Join Chris and Fred as they discuss product feasibility when it is nothing more than a concept.  There is a lot to unpack here! This comes from a question raised by a Singaporean listener who is a student looking at the feasibility of a portable device that repels mosquitoes, utilizing cutting-edge technology, including the ability to detect the unique frequencies of flying mosquitoes. Topics include: Hand-held devices get abused … a lot … without being abused. Engineers are routinely amazed by how people can drop, squash, bump, heat, chill, and otherwise do challenging things to it. The fact is, this happens when people aren’t trying to abuse handheld devices. So, start by never underestimating the trials and tribulations of handheld devices! You can’t be organization ‘agnostic.’ What is feasible for SpaceX is not feasible for a young startup with less than $ 500 000 in working capital. So, you need to determine what your organization can do, and if you are trying to get a larger company to buy your idea after you have created a proof of concept, and so on. Then the technology. Does it repel mosquitoes? You don’t need to build a working prototype to replicate the ‘technological tactics’ your final product will hopefully use to repel mosquitoes. But if the answer is ‘yes’ … don’t stop thinking! Fred discussed an example where a wearable health device had 50,000 units (out of 70,000) returned by customers in the first month because the recharging socket was not waterproof. The product was feasible, AND it is really easy to waterproof recharging sockets. They just didn’t do it! 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 1083 Portable Device Feasibility appeared first on Accendo Reliability.

Equations for Goal Setting Abstract Chris and Fred discuss what equations (if any) exist for setting and optimizing reliability goals … sometimes trading off against other goals. Wo … Key Points Join Chris and Fred as they discuss equations that exist to help you come up with and optimize reliability goals and targets. This comes from a listener who points out that well-known reliability software contains equations based on Weibull distributions, optimization algorithms, and perhaps alchemy that can do all this for you. What do we think? Topics include: Reliability doesn’t always cost more. This is important. Many producers that successfully implement a quality and reliability improvement initiative tend to magically spend less money on product development, and take less time to do it. That’s right, you can improve reliability, reduce costs, and speed up time to market all at the same time. How? Quality and reliability initiatives tend to eliminate crises and issues during production that otherwise cost time and money. Hewlett-Packard famously did this during the 1980s, reducing warranty returns by a factor of eight, while reducing production costs and time to market.  Remember this … Reliability optimization frameworks tend to assume reliabiltity costs more. Which isn’t always true (as above). You will often see university level equation frameworks where models that link increased reliability with increased costs … pretty much always. Which immediately invalidates them. And then there is market share … While it is generally true that things like market share are dependent on reliability, this relationship can sometimes be weak. While customers will tend to buy more reliable products at similar products, they need to find out about it. If two products offer a 2-year warranty period, then the customer is not provided any other information on reliabiltiy to help them prefer one over the other. If one of these products is more reliable than the other, the same warranty period effectively hides this. And then there is the dodgy mathematics and statistics. The example in quesiton used the Weibull distribution to model market share. Without justification. The takeaway? Just because a website or a textbook as an equation that alledgedly optimize reliabiltiy goals with retail costs and everything else … doesn’t mean it is valid. Not even a little bit. If there are equations, ask why they are valid. The Weibull distribution is great at modelling fatigue failure mechanisms. But market share??? Come on … 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 1082 Equations for Goal Setting appeared first on Accendo Reliability.

Customer Requirements Abstract Chris and Fred discuss customer requirements when it comes to reliability. How do we get this wrong? Key Points Join Chris and Fred as they discuss requirements … not just yours … when it comes to reliability. What can go wrong? Topics include: MTBF and other wrong metrics. People love the MTBF because it is simple, a single number, and it feels like it represents ‘reliability’ (but it does not). Sometimes we try hard to convince people not to use it, but they still want to. AND … they still want to ask ‘will this work (or not)?’ Pick one. And, of course, those who specify the MTBF usually come back later, bemused, when something fails. What is reliability then? Reliability is the probability that something will not fail within a particular duration under specified conditions. For example, we might be interested in the warranty reliability of a product. If the warranty period is 2 years, then the warranty reliability requirement presumes this is the particular duration. What if a product has an MTBF of 2.5 years … what fraction of products will fail in the warranty period? The answer lies somewhere between 0% and 77%. What can you do? Try to work with people. If they use a crazy metric to describe required reliability performance … try and tell them what that actually means. Tell them that requiring an MTBF of 2.5 years because we want to limit failures during our 2-year warranty period … actually means anywhere between 0 and 77 % of products will fail during that warranty period … and if that doesn’t work, maybe it’s them and not 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 1081 Customer Requirements appeared first on Accendo Reliability.

Bearing Failure and Analysis Abstract Chris and Fred discuss how bearings fail. Bearings are among the most common components used in products and systems. So, how do they go wrong? Key Points Join Chris and Fred as they discuss how bearings fail, in response to a question from one of our listeners whose organization has experienced some bearing failures in wind turbines (all of which were caused by ‘systemic’ or endemic root causes). So, how do bearings fail? Topics include: Simple answer – spalling. Spalling is a type of fatigue unique to bearings, caused by the slight friction forces that the rotating balls exert on the race surface they roll over. Spalling leads to pitting, which increases friction, which in turn heats things up, causing them to expand, which adds stresses, and ultimately accelerates the growth of cracks and pits, until the ball bearing (in many cases) literally explodes. And when it comes to testing or life data analysis … you often test or observe bearings where a number have failed … leaving a number that is still working. The times at which we last observed those to be still working are what we call ‘censored data points’ and need to be included in the analysis. How can you predict the times at which bearings will fail by inspection? With difficulty. Non-Destructive Inspection (NDI) is often used to measure the depth of fatigue cracks, but it becomes challenging with bearings. You need to pull the balls or rollers out and then look at the races they roll over. This is very challenging. Vibration analysis provides a warning of impending failure, as those pits often cause vibration. Until pits appear, you are blind! What about refurbishment? We do that with a log with ‘big’ bearings. But does the refurbishment make the bearing as good as new? … as good as old? … as good as something in between? This comes from what we call the ‘general renewal’ theory, and it misses the maintenance-induced failures that you get whenever you perform maintenance. So what do you do? Do whatever works best to understand how your system fails. Perhaps you could consider degradation modeling, or utilize your existing data (if you have a large dataset), or explore alternative approaches. 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 1080 Bearing Failure and Analysis appeared first on Accendo Reliability.