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Why is PoF so Hard?
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Why is PoF so Hard?
Abstract
Chris and Fred discuss why the Physics of Failure (PoF) is hard to model? … or is it?
Key Points
Join Chris and Fred as they discuss how the Physics of Failure (PoF) is seen as hard to use to model time to failure of something. It usually needs a detailed equation or formula to model how long it takes for something to fail based on physical parameters like grain size, modulus, strain exponent and so on. Sounds hard!
Topics include:
- What does PoF mean? It means that instead of doing things like testing products until failure to see the spread of times to failure (as in, how probability is distributed), an ‘accurate’ model that might have lots of parameters based on material properties is used instead of teasing to quickly and accurately model time to failure.
- So what’s the problem? It can be really, really hard to know which of the thousands of complex equations are the one(s) that describe how your product fails. There are resources out there that have huge lists of PoF models (and their detailed equations) for you to pick from. But then … how do you know which one perfectly captures the way your thing fails?
- Then there are the parameters. Some PoF models require tens of parameters to be known. But if you don’t know what these parameters are … you are in trouble. Some people just ‘guess’ these parameters based on similar materials or scenarios. The problem with this is now that you are modeling someone else’s failure that may or may not be similar to yours.
- But we do use PoF more than we might think. When we do Accelerated Life Testing (ALT), we often use what we call ‘Arhennius Plots.’ These are charts that happen to make it really easy for us to see and model how increasing the temperature of a product speeds up the failure process. This allows us to ‘accelerate’ testing by increasing temperature to not have to spend 10 years testing products to understand service reliability. But … ‘Arhennius Plots’ only work for failure mechanisms that are based on chemical reactions (like corrosion, dendritic growth and so on). And many people try and use ‘Arrhenius Plots’ for things that are not chemical reactions.
- Again … work out what decision you are trying to inform. This will help you see if you need to understand PoF, do your own test, use expert judgment or anything else!
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.
Show Notes
The post SOR 966 Why is PoF so Hard? appeared first on Accendo Reliability.
650 episodes
Fetch error
Hmmm there seems to be a problem fetching this series right now. Last successful fetch was on September 02, 2024 16:33 ()
What now? This series will be checked again in the next day. If you believe it should be working, please verify the publisher's feed link below is valid and includes actual episode links. You can contact support to request the feed be immediately fetched.
Manage episode 418695404 series 2359263
Why is PoF so Hard?
Abstract
Chris and Fred discuss why the Physics of Failure (PoF) is hard to model? … or is it?
Key Points
Join Chris and Fred as they discuss how the Physics of Failure (PoF) is seen as hard to use to model time to failure of something. It usually needs a detailed equation or formula to model how long it takes for something to fail based on physical parameters like grain size, modulus, strain exponent and so on. Sounds hard!
Topics include:
- What does PoF mean? It means that instead of doing things like testing products until failure to see the spread of times to failure (as in, how probability is distributed), an ‘accurate’ model that might have lots of parameters based on material properties is used instead of teasing to quickly and accurately model time to failure.
- So what’s the problem? It can be really, really hard to know which of the thousands of complex equations are the one(s) that describe how your product fails. There are resources out there that have huge lists of PoF models (and their detailed equations) for you to pick from. But then … how do you know which one perfectly captures the way your thing fails?
- Then there are the parameters. Some PoF models require tens of parameters to be known. But if you don’t know what these parameters are … you are in trouble. Some people just ‘guess’ these parameters based on similar materials or scenarios. The problem with this is now that you are modeling someone else’s failure that may or may not be similar to yours.
- But we do use PoF more than we might think. When we do Accelerated Life Testing (ALT), we often use what we call ‘Arhennius Plots.’ These are charts that happen to make it really easy for us to see and model how increasing the temperature of a product speeds up the failure process. This allows us to ‘accelerate’ testing by increasing temperature to not have to spend 10 years testing products to understand service reliability. But … ‘Arhennius Plots’ only work for failure mechanisms that are based on chemical reactions (like corrosion, dendritic growth and so on). And many people try and use ‘Arrhenius Plots’ for things that are not chemical reactions.
- Again … work out what decision you are trying to inform. This will help you see if you need to understand PoF, do your own test, use expert judgment or anything else!
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.
Show Notes
The post SOR 966 Why is PoF so Hard? appeared first on Accendo Reliability.
650 episodes
All episodes
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