Some statistical SW packages offer the ability to compare two or more sets of reliability or life data in order to determine which of the data sets has a more favorable life distribution. The data sets could be from two alternate designs, manufacturers, lots, assembly lines, etc. The data sets may contain censored data. In general, the problem boils down to that of being able to determine any statistically significant difference between the two (or more) samples of potentially censored data from two possibly different populations. These tools comes to mind:
(a) Contour Plots: To determine whether two data sets are significantly different and at what confidence level, one can utilize the contour plots. By overlaying two contour plots from two different data sets at the same confidence level, one can visually assess whether the data sets are significantly different at that confidence level if there is no overlap on the contours (were the same distribution must be fitted to both data sets).
(b) Life Comparison Tool: suggested by Gerald G. Brown and Herbert C. Rutemiller, to estimate the probability of whether the times-to-failure of one population are better or worse than the times-to-failure of the second (could be from differnt distributions). The same tool could be used to perform Stress-Strength analysis.
Does JMP13 (or future JMP 14) provide any of these tools in their standard or Pro versions?
interesting question: for comparing two different distributions, JMP has a built in function called Life Distribution that can handle different groups of observations, as in the example from the documentation that you can find here: https://www.jmp.com/support/help/13-2/Examine_the_Same_Distribution_across_Groups.shtml#1326983
There is also the chance of comparing different life distributions according to different causes,as in this another example: https://www.jmp.com/support/help/13-2/Omit_Competing_Causes.shtml#1298294.
In our Mastering JMP webcast series there is also a recorded webcast on these topics:
However, what I suggest you is to submit your question as-is in the much broader JMP world wide community as a general discussion, so that it will be seen by other JMP reliability experst.