Component Fatigue Data Statistical Analysis
Component Fatigue Data Statistical Analysis
(OP)
Hello,
I am looking for some statistical methods that may be applicable to a study that I am performing. I am currently performing some vibratory high cycle fatigue (HCF) testing on some parts in a 1F mode. I need to demonstrate that the parts have a certain amount of HCF strength, for example 10 ksi. So far I have tested 9 parts and all parts have demonstrated to "runout or pass" at 15 ksi or above. The issue that I have is that I have been unable to break the parts in the mode of interest; unfortunately changing the mode is not an option. If I were able to break the parts, that would tell me what the actual HCF strength is. Instead, once I get to levels between 20 ksi – 35 ksi, varies for each part, the part starts coupling and I can no longer run in the mode of interest.
Enough background, here is my statistical question. The two options that I think I have with the current data is to perform some type statistical analysis that analyzes the go no-go data (I have 9 parts that pass and 0 parts that do not, what does this tell me statistically) or I could do some type of analysis that uses the known minimum HCF levels that I have determined for each part (for example, I know that 4 of the parts that have a strength of at least 15 ksi, 3 parts have a strength of at least 20 ksi, 1 part has a strength of at least 25 ksi, and one part has a strength of at least 35 ksi). If anyone has any ideas on some type of statistical analysis that I can do to demonstrate that I have plenty of HCF margin (compared to my 10 ksi requirement) which would give me confidence when these parts start in production that I will always meet my 10 ksi limit, please feel free to share. If there are other types of options that may be applicable for my study, please also share those ideas.
I have also posted this in the Statistics forum.
Thank you.
I am looking for some statistical methods that may be applicable to a study that I am performing. I am currently performing some vibratory high cycle fatigue (HCF) testing on some parts in a 1F mode. I need to demonstrate that the parts have a certain amount of HCF strength, for example 10 ksi. So far I have tested 9 parts and all parts have demonstrated to "runout or pass" at 15 ksi or above. The issue that I have is that I have been unable to break the parts in the mode of interest; unfortunately changing the mode is not an option. If I were able to break the parts, that would tell me what the actual HCF strength is. Instead, once I get to levels between 20 ksi – 35 ksi, varies for each part, the part starts coupling and I can no longer run in the mode of interest.
Enough background, here is my statistical question. The two options that I think I have with the current data is to perform some type statistical analysis that analyzes the go no-go data (I have 9 parts that pass and 0 parts that do not, what does this tell me statistically) or I could do some type of analysis that uses the known minimum HCF levels that I have determined for each part (for example, I know that 4 of the parts that have a strength of at least 15 ksi, 3 parts have a strength of at least 20 ksi, 1 part has a strength of at least 25 ksi, and one part has a strength of at least 35 ksi). If anyone has any ideas on some type of statistical analysis that I can do to demonstrate that I have plenty of HCF margin (compared to my 10 ksi requirement) which would give me confidence when these parts start in production that I will always meet my 10 ksi limit, please feel free to share. If there are other types of options that may be applicable for my study, please also share those ideas.
I have also posted this in the Statistics forum.
Thank you.





RE: Component Fatigue Data Statistical Analysis
Cheers
Greg Locock
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RE: Component Fatigue Data Statistical Analysis
Courtesy of metengr
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RE: Component Fatigue Data Statistical Analysis
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Cory
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RE: Component Fatigue Data Statistical Analysis
Thanks
RE: Component Fatigue Data Statistical Analysis
Cheers
Greg Locock
SIG:Please see FAQ731-376: Eng-Tips.com Forum Policies for tips on how to make the best use of Eng-Tips.
RE: Component Fatigue Data Statistical Analysis
RE: Component Fatigue Data Statistical Analysis
Cheers
Greg Locock
SIG:Please see FAQ731-376: Eng-Tips.com Forum Policies for tips on how to make the best use of Eng-Tips.
RE: Component Fatigue Data Statistical Analysis
RE: Component Fatigue Data Statistical Analysis
http
Google "staircase fatigue" for more info.
RE: Component Fatigue Data Statistical Analysis
Are all your samples from the same batch? Multiple batches could give you more confidence and explain your scatter. I'm curious why there is such a spread in the level in which the parts couple?
Can you do some other mechanical test to help quantify the material? My first thought is some type of pull test.
ISZ
RE: Component Fatigue Data Statistical Analysis
Weibull's seminal paper doesn't really discuss in terms of time: http://www.barringer1.com/aug01prb.htm
Lots of stuff on the Barringer website: http://www.barringer1.com/wa.htm
http://www.barringer1.com/Papers.htm
TTFN
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