Drawing conclusions when you have few or no failures
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When you have few or no failures, you can use historical values for distribution parameters to improve your analysis. Providing historical parameters makes the resulting analysis more precise, if your values are an appropriate choice.

If your data come from a Weibull or exponential distribution, you can do a Bayes analysis to obtain lower confidence bounds for parameters, percentiles, survival probabilities, and cumulative failure probabilities.

If you collect life data and have no failures, Minitab can still analyze when all of the following are met:

·    The data come from a Weibull or exponential distribution.

·    The data are right-censored.

·    The maximum likelihood method will be used to estimate parameters.

·    You provide a historical value for the shape parameter (Weibull).
If your data are from an exponential distribution, Minitab automatically assigns a shape parameter of 1.

For example, your reliability specifications require that the 5th percentile is at least 12 months. You run a Bayes analysis on data with no failures, and then examine the lower confidence bound to substantiate that the product is at least as good as specifications require. If the lower confidence bound for the 5th percentile is 13.1 months, you conclude that your product meets specifications and terminate the test. See Demonstration Test Plans to determine the optimal testing time or number of test units to use.