Geoffrey_Coram
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I don't think this is going to work the way you think.
Suppose your process has TOX and VFB varying for the different corners (probably, there are other parameters also, but let's keep it simple). If you assume the TOX for the SS and FF corners define the 3-sigma points of the TOX distribution, and similarly for VFB, then the MC distribution you end up with will be *very* unlikely to hit the 3-sigma points on *both* of those independent variables.
If you try to pick the SS, FF corners as 3-sigma points of the combined distribution, you'll have to make some guesses as to the relative effects of the different parameters: is the "speed" strongly dependent on TOX, but TOX is tightly controlled, or is it weakly dependent on TOX that is poorly controlled?
Let's pretend that you add the sigmas of the two parameters to get the sigma of the MC distribution (I'm sure the math is more complicated, but I think this can illustrate my point without making me spend the time to do the derivation): the 3-sigma point of the MC distribution could be: a) the 2-sigma point of TOX plus the 1-sigma point of VFB b) the 1-sigma point of TOX plus the 2-sigma point of VFB c) the 0.1-sigma point of TOX plus the 2.9-sigma point of VFB
and you can see that the corners are really insufficient for making any kind of assumption about the real distributions.
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