Your Reliability Engineering Professional Development Site
Chris and Fred discuss an ALT or Accelerate Life Test Design Question. We love these podcasts … as we are directly answering a question from one of our listeners. Interested in hearing a response to a real-world question from a listener?
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Carl and Fred discussing a reader question about FMEAs. Specifically, whether reliability predictions (for similar systems) are valid input to the Occurrence rating in an FMEA.
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When trying to fit a probability distribution to quantitative results, sometimes the normal probability doesn’t fit. Minitab has a wealth of distributions to pick from. Do you just pick whichever one Minitab tells you fits the best? Maybe not. Just because the distribution fits your data doesn’t mean it’s a good one to use. We review my top 3 distributions for product testing and some other ones that come up but may not be appropriate to use.
We’ll also share what you need to think about when picking a distribution:
Greg and Fred discussing the right method (s) to solve quality and reliability problems specifically answering the question ‘is the approach good enough?’
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Kirk and Fred discuss the use of artificial intelligence engines such as ChatGPT in Reliability Engineering. A copy of the ChatGPT questions and responses that we discuss on this podcast is listed in the show notes below.
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How do you look at any product? See just a thing that performs a certain function? In this episode I discuss my perspective on how I see a product – as an assembly of materials – and how it influences how I help design products to meet performance, reliability, and cost goals.
SHOW NOTES
In this special episode of Quality during Design Redux, we’re pulling episodes from our archive about test results analysis.
Originally released May 2021. We talk about the importance of examining failure modes plus other topics.
If we’re not careful with or ignore failure modes, we can choose the wrong reliability model or statistical distribution. If our product performance is close to the required limits and/or we need a very accurate model, this could be a big problem.
We talk about the importance of failure modes and step-through a tensile-test example to explore these other topics:
What is supportability? Is it working out how many spare parts you will need (and when)? No. Is it working out how many maintainers or technicians you will need to keep your system working? Still no. What about working out what tools these maintainers or technicians need? No again. But many people think that this is what ‘supportability’ is. ‘Supportability’ is actually a characteristic of your product or system. Is the ‘ability’ for it to be ‘supported.’ And this can mean different things in different scenarios. It is also not a ‘number.’ If you have two comparable systems, but one needs fewer spare parts, is easier to maintain, needs fewer tools, has lots of sensors that give plenty of warning for maintenance, and so on … then it might be more supportable. But the main thing you need to ‘think about’ regarding supportability is that because it is a characteristic of a product or system … it has to be baked INTO the design. Want to learn more about how to do this? Join us for this webinar.
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The subjects of Industry 4.0 and Big Data have been widely discussed on this podcast. What is Industry 4.0? What data is our industry collecting? And, perhaps more importantly, how can we sift through all of that data to make it useful and actionable?
To help answer these and other data-related questions, I invited Ryan Gamble, CEO and Founder of Intraratio on this episode. Intraratio Corporation is a company that provides on-premise and cloud hybrid software with platforms to track, manage, control, and automate the manufacture of advanced electronics. Intraratio serves the semiconductor, SMT, space/military, medical device and EV markets. Ryan earned a dual Electrical and Computer Engineering degree and spent many years in the semiconductor industry. He’s responsible for improving product manufacturing and testing of commercial and space/military product lines including multi-core DSP, RF and Silicon Photonics devices. During this period he developed software systems to automate and manage quality and reliability of complex electronics, extending this to hyperscale web based platforms that interconnect factories globally.
His passion is working with all levels, to identify and recommend solutions to business problems, based on a deep technical understanding of operational processes and product complexities.
Ryan’s Contact Info:
rgamble@intraratio.com
https://www.intraratio.com
Kirk and Fred discussing Kirk’s recent trip to the Texas Pinball Festival (TPF) and the reliability of Pinball Machines which new designs have been produced for over six decades. Some of the mechanical assemblies have not changed in design for those many decades, even though some changes would be simple and useful, but change is difficult in this very small group of manufacturers.
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Carl and Fred discussing the second step in achieving high reliability: “Develop a Reliability Gap Assessment.”
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SHOW NOTES
In this special episode of Quality during Design Redux, we’re pulling episodes from our archive about test results analysis.
In our Season 1 episode titled “The Fundamental Thing to Know from Statistics for Design Engineering”, we talked about hypothesis testing: how it is used for lots of data analysis techniques.
The next 4 episodes of this QDD Redux are taking the next steps.
In this episode we review sampling for design tests. We talk through a generic thought process for choosing a statistically relevant sample size and propose some basics that we can all learn about to better understand sampling.
Our goal is for us to be able to better talk through a sampling scenario with our quality and reliability engineering friends, and to better prepare for the information that they’re going to want to know when asked, “How many do we need to test?”
Carl and Fred discussing the first step in achieving high reliability: “Develop a Reliability Strategic Vision.”
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Chris and Fred discuss the importance of understanding value when you make decisions. And value needs to mean something to you and your organization. Not something in a dictionary.
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In this episode I discuss learning and professional development. There’s so much to know to be an engineer and college courses cover the tip of the iceberg, even if you go to grad school. I learned this early in my career as I was faced with decisions and problems related to topics that I never encountered in school. I also learned that I had to shoulder the responsibility of learning the topics. Some of the learning came from colleagues, some came from taking short courses, and some came from reading textbooks and technical journals. In this episode I discuss my learning experiences and philosophy about learning, the pitfalls of relying on learning just from experience, and resources for learning and professional development.
