In a past life I tried to normalize this by adding the standard deviation of the rolling averages.  And then triggered off of the new average.  I also do not use rework in yield calculations at all.  The yield info is first pass data. 
 
Kat


>>> [log in to unmask] 12/27/02 12:09PM >>>
Does anyone have a standard way to normalize yield percentage charts for
wildly varying production volumes ?
My yield percentage charts show 50% yield when there is 1 out of 2
failures or 50 out of 100 failures.
The 50% Yield with 1 out of 2 usually happens during a Christmas week
when there is no production, only rework.
I have tried to normalize the charts by using a constant denominator
based on the nominal volume.
I use 13 week rolling averages but they are messed up by the low volume
yield results.
This low volume percentage reporting can cause incorrect corrective
actions.
Does anyone know of a standard way to normalize the data ?
Cronbach's Alpha,
Split-Half Reliability (Spearman-Brown Coefficient),
Attenuation correction,
Pair Wise Deletion of Missing Data,
Partial correlation,
Parzen Window,
Pearson Curves,
Johnson Curves ?

Paul Signorelli

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