How to Adjust Parameters to Achieve MTBF
A troublesome question arrived via email the other day. The author wanted to know if I knew how and could help them adjust the parameters of a parts count prediction such that they arrived at the customer’s required MTBF value.
I was blunt with my response.
My response should have been that they should focus on the improving the reliability of the design and not worry about the results of a 217 based prediction.
The list of issues in the question
- Using MTBF to specify reliability
- Using MTBF to measure reliability
- Using 217 based parts count approach to estimate field reliability
- Attempting to adjust or tweak parts count calculations to improve results
—There are undoubtedly other issues, yet let’s address these first.
Using MTBF to specify reliability
Stop it. MTBF is only an average failure rate and without a duration has little meaning. Even with a duration it isn’t very informative and doesn’t help us to address the requirements for an early life or mission duration, warranty or deployment duration, or useful or expected lifetime duration. We can ignore early life failures and wear out failures as long as the overall average is fine. It also permits us to test assuming the exponential distribution, thus avoiding having to test long enough to reveal wear out mechanisms.
Using MTBF to measure reliability
Hopefully they are using other methods to estimate reliability other than just a parts count database. Either way, using MTBF masks the nature of the failures over time. MTBF is an average and there are many ways to achieve a specific MTBF value. Instead, use reliability and the underlying life distributions which detail the changing nature of the expected failure rates with time and/or stress.
Using 217 based parts count approach to estimate field reliability
Mil Hdbk 217F and similar parts count methods are not tools to predict field performance. The descriptions and list of objectives for such a study clearly state so (in the various parts count tools I’ve encountered). The tool is to permit comparisons, to explore impact of design changes, etc. Specifically not to compare to performance requirements or to estimate actual field failure rates.
It is the wrong tool, so stop using it as a means to estimate reliability.
Attempting to adjust or tweak parts count calculations to improve results
Having played with and used different parts count methods over the years I’ve found that there are plenty of ways to adjust and modify the results. Derating factors, quality factors, temperature assumptions, etc. The list is endless with some tools. In theory we have all the information and can includes the various modifiers to improve the ability to the prediction to reveal weaknesses and the impact of changes.
Using fewer parts or running electronics at a cooler temperature in general will improve system reliability. That is one very good thing about parts count predictions, it encourages changes that are actually good for the reliable perform of the system. Using the result as an estimate of future performance has been shown over and over again to have no merit.
Fiddling with settings and assumptions is just repugnant and most likely ethically wrong according to any engineering code of ethics. We are not in the business of adjusting calculations to get the desired results, we use the available tools to best of our ability and make decisions accordingly. If the results are not good enough (despite not relevant or useful as in this case) we should not adjust the assumptions and setting to get the desired result.
That is just wrong.
Instead focus on creating a reliable design that meets the customer expectations. If the requirement is MTBF ask what they really want in terms of reliability. Use physics of failure and life testing techniques to estimate future performance. Provide the customer with useful information and if absolutely required include the MTBF with how that came about from the actually useful information.