Rick,
The long term issue of Cpk and Ppk often become irrelevant if your process is under statistical control. If your process is under control, and has been for a while, and it shows no sign of deviating from being under control (as per control charts and so forth) then what happens is that your actual process variance, calculated from the raw data, and the sigma_hat, the estimated variance (from Rbar/d2) become more or less similar.
As a result, you can use either one to give a fair picture of short- and reasonably long-term process capabilities. One thing to note, I have worked with companies that require Ppk as well as Cpk presented side by side.
Also, I don’t mean to start a flame war here or anything, but from what I have had experience with, I don’t think Cpk is going to go out soon.
Also, if I may quote you from your previous post :
“If Cpk goes up, you need to explain why? If Cpk goes down, should I get a bonus? “
I find this rather perplexing. The aim of studying your process, is to increase Cpk (1.33 is a nice number but the higher the better). Your statement seems to read otherwise. Cpk is obtained by dividing by variation, so the smaller the variation the better, and hence the smaller the Cpk.
As per the ‘snapshot’ comment, a process under statistical control will report similar (or if a source of common cause variation is found and eliminated, increased) values of both Cpk and Ppk. So, Cpk and Ppk can both be used as a long term indicator of process capability and performance if and only if your process is under statistical control. It becomes a snapshot only if your process is not under statistical control, because your process is subject to random causes of variation (a.k.a. special causes).
Since the use of these indices is statistical in nature in the first place, and there are robust theories behind them, I think you should not say such things about statisticians (I am an engineer myself.). Just one more thing to be said about statistics, is that the sigma = Rbar/d2 generally gives an overestimate of the sigma_hat calculated from the raw data. This is a consequence of Shewart methods.
Personally, I think that Cpk is the better one to use, simply because (as Rick said) more people know about it, and have a better idea of what it stands for.
