Publication date: 08/13/2020

The reliability demonstration depends on the assumed failure time distribution with scale parameter σ. The reliability standard, or probability of survival at time t and location μ is stated as follows:

where μ is solved for using the following:

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To calculate sample size and the size of the test, the probability of survival at time t is posed as a hypothesis test:

where p* is the standard probability of survival at time t*.

We want to test the hypothesis at the α level or as follows:

α = Pr(k or few failures | H0 true).

Since the test is of n independent units, the number of failures has a binomial (n, p) distribution where p is the probability of a unit failing before time t. Therefore, we can express α as a function of t and n:

where μ* and σ* are from the assumed reliability standard.

Properties of the binomial and beta distributions result in being able to solve for t using:

For n, Brent’s method is used to find the root of:

where:

B−1(α; n − k, k + 1) is the α quantile of the Beta(n − k; k + 1) distribution

and Φ() is the cumulative distribution function of the assumed failure time distribution.

For more information about calculations in JMP, see Barker (2011, Section 5).

Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).

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