Easy to do. I am assuming that each component or event is independent of each other, and that "failure" is that the time to event is less than a desired time. You can just create two columns in a data table with the Random Weibull() function in the column. Then you can use another column to test to see if both components failed before a given time.
Maybe a simpler way is to just use basic probability calculations. If T1 is the time to failure for component 1, T2 the time to failure for component 2, then the time to failure for both to happen at the same time is Tmax=max(T1, T2). Let F be the cumulative distribution function for T1 or T2 [F(t) = Prob (T1 < t)]. The cumulative distribution function of the maximum of two identically distributed and independent random variables is just Fmax(t) = [F(t)]^2.
To sample from any probability distribution, if you know the cumulative distribution function, you can use this approach.
- generate a random uniform value (uniform random on the interval [0,1]), U
- Find Tmax such that U=Fmax(Tmax) --> this will be your random variable from the "double weibull" distribution
in the cause above, Fmax(t) = [F(t)]^2, so solving for Tmax is just
U=Fmax(Tmax)=[F(Tmax)]^2
sqrt(U) = F(Tmax)
You can use the Weibull Quantile() function in JMP to find Tmax
alpha=1;
beta=1;
// generate random "Double Weibull"
Tmax = Weibull Quantile(Random Uniform(),alpha, beta);
You could use that formula in a column in a data table, or make a JMP script to generate the random draws.
Alternatively, if you have JMP Pro, you can use the Reliability Block Diagram platform to easily see the distribution of failure time for this "K out of N" system.