Understanding subgroup sizes for Six Sigma



My company is making plans to tranistion to Six Sigma processes, so I
purchased Pyzdek's book from Amazon to try and get a grip of it. My
statistics education is a couple decades old at this point, but I
think Pyzdek's wording is quite vague and is causing some of my
confusion.

On the topic of subgroups and control charts, an example is presented
with the typical Six Sigma "out of control" probability of .0027. He
then goes on to suggest that the probability of an "out of control
indication is 1/.0027 = every 370 units which I completely understand,
but then he says that the subgroup size will dramatically lower this
probability and allow the operator to detect changes more quickly.

What I don't understand, and he doesn't explain, is how can I quantify
how "dramatically" it will change? If I'm using standard SS control
limits of .0027, how/why would changing my subgroup size from say, 5,
to 10, 20, or even 50 make a difference in the probability that one of
the averages is "out of control"? My intuition, which is obviously
wrong, tells me that each of the 5, 10, 20, or 50 subgroup averages is
equally likely to plot outside the control limits.

Any help, equations, or pointers to material I could review would be
greatly appreciated. Suggestions for a better beginner book would
also be appreciated. (More examples!)
.



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