Your Reliability Engineering Professional Development Site
The lognormal distribution has two parameters, μ and σ. These are not the same as mean and standard deviation, which is the subject of another post, yet they describe the distribution, including the reliability function.
$$ \displaystyle R(t)=1-\Phi \left( \frac{\ln (t)-\mu }{\sigma } \right)$$
Where Φ is the standard normal cumulative distribution function, and t is time. [Read more…]
Let’s make a comparison. Let’s check our product’s key characteristics against specifications, compare vendor life data, or compare the newest design changes to prior performance. We can and should do comparisons well using the appropriate statistical approach.
Let’s examine a handful of parametric and non-parametric comparison tools, including various hypothesis tests. Plus how to best use these tools and when to set them aside and explore another approach.
The Linkedin NoMTBF group is growing and while not very active does have an occasional interesting discussion. Join the discussion and maybe relate how you have raised awareness around the proper use of MTBF.
https://www.linkedin.com/groups/1857182/
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It took us years to move from top-down to people-centric management, but the journey was worth it Peter Drucker once said, “Culture eats strategy for breakfast.” Throughout my career, I have spent a lot of time in the strategy room. But no matter what we decided there, until we got the organizational culture right, we were unsuccessful in executing our goals.
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The following is a recent discussion on the sister Linkedin NoMTBF Group. It was and may continue to be a great discussion. Please take a look and comment on where you stand. Do you have some form of the Arrhenius reaction rate equation in your reliability engineering work? Join the discussion here with a comment or on the Linkedin group conversion.
Fred
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An excellent short white paper by Craig Hillman that is worth reading. It underscores why I claim HALT is the second worst 4 letter acronym in our profession.
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Calculating and interpreting the process capability ratios is the easy part. Getting valid results takes more work and thinking. Knowing that the process is capable is only one use of this information. We should also use the information contained in these ratios to inform product design tolerance. [Read more…]
Hello, can anyone advise me how to calculate temperature acceleration factor for a complex system including cards, RF elements, cables, motors and moving parts? Is the Arrhenius model valid for such systems, or there are more precise models? Thank you!
[Read more…]Fred i was asked this question and wanted to know what your thoughts were on this. R and D asked me what was the criteria to decide if to test at a component level or at a system level , my answer was that it should depend on what is the reliability and confidence level of the component
your thoughts?
thanks
sd
Just a short post to point to a paper on the accuracy of part count prediction techniques. A few years ago, I recalled seeing a paper that studied the difference between various parts count methods and actual results.
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With the kind permission of Wayne Nelson and Robert Abernathy, we are posting an article on the analysis of repair data. As you may know, the assumptions made when using simple time-to-failure analysis of repairable systems may provide misleading results. Using the analysis method outlined by Wayne is one way to avoid those costly mistakes.
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On one of my first vendor visits, they proudly showed us the control charts behind glass near the conference room. They were nicely printed, all in perfect control, and rather odd. A control chart belongs on the production line, where the operators make the measurements. They are of little value when automatically collected and printed out once a month for display-only purposes. [Read more…]
Giving a presentation last week and asked if anyone uses an 85%RH/85°C type test, and a couple indicated they did. I then asked why.
The response was – just because. We have always done it, or it’s a standard, or customers expected it. The most honest response was, ‘I don’t know’.
Why is the test being done? Who is using the information for a decision? What is the value of the test results? If ‘just because’ is the best you can say about a test, why do it?
I’ve often railed on and on about the inappropriate use of MTBF over Reliability. The often cited rationale is, “it is simpler”. And, I agree, making simplifications is often necessary for any engineering analysis.
It goes too far when there isn’t any reason to knowingly simply when the results are misleading, inaccurate or simply wrong. The cost of making a poor decision based on faulty analysis is inexcusable.
During RAMS this year, Wayne Nelson made the point that language matters. One specific example was the substitution of ‘convincing’ for ‘statistically significant’ in an effort to clearly convey the ability of a test result to sway the reader. For example ‘the test data clearly demonstrates…’
As reliability professionals let’s say what we mean in a clear and unambiguous manner.
Thus, you may suspect, this topic is related to MTBF.
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