I ran across a cool set of tools for computing reliability properties, including reliability improvements due to redundancy, MTBF based on testing data, availability, spares provisioning, and all sorts of things. The interfaces are simple but useful, and the tools are a lot easier than looking up the math and doing the calculations from scratch. If you need to do anything with reliability it's worth a look:
http://reliabilityanalyticstoolkit.appspot.com
The one I like the most right now is the one that tells you how long to test to determine MTBF based on test data, even if you don't see any failures in testing:
http://reliabilityanalyticstoolkit.appspot.com/mtbf_test_calculator
Here is a nice rule of thumb based on the results of that tool. If you want to use testing to ensure that MTBF is at least some value X, you need to test about 3 times longer than X without ANY failures being observed. That's a lot of testing! If you do observe a failure, you have to test even longer to determine if it was an unlucky break or whether MTBF is smaller than it needs to be. (This rule of thumb assumes 95% confidence level and no testing failures observed -- as well as random independent failures. Play with the tool to evaluate other scenarios.)
Companion blog to the book Better Embedded System Software by Phil Koopman at Carnegie Mellon University
Monday, June 4, 2012
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