I want to echo Victor_G's comments. I realize there may be misunderstandings due to different languages, so little patience on everyone's part would be helpful. For me - given the current heated political climate in the US - I do not appreciate the CAPS and strident comments. It is too familiar to particular presidential candidates and the bullying that goes on. What I don't understand from your comments is exactly what you find wrong with JMP's control charts. I honestly don't know, so you should tell us so that we can either help you or see what JMP is doing wrong. Further, I am quite familiar with the exponential distribution, but I'm not sure what that is relevant to the control chart. As was said, the control chart assumes not particular distribution. If you know your data is supposed to come from an exponential distribution, then there are ways to see how close the data is to that distribution - but the control chart is examining the data over time rather than a time-invariant distribution. I think to combine the two (a known distribution and a control chart) might benefit from some processing of the data before making the control chart. For example, you might examine the deviations from a particular exponential distribution and plot these in a control chart - I don't have the medical background to know what the supposed exponential distribution would look like.
