Dave,

I suppose a X/MR chart could be used but I'm not sure what validity the statistical values would have.  Since the data from a variables data chart is intended to be retrieved from a population or process that has the same basic variable elements, I don't see the how the inherent distribution representing many different lots and variables would be normal.  I suppose if the distribution of the different percentages were normal, then the data collected could have some statistical validity.  Otherwise, I think you will end up with limits without any real meaning. Basically you would be simply plotting performance, 

Since performance plotting is the only way I use attribute data, I simply recommend plotting a P chart without the stat limits and monitor it only for trends. ( You don't need control limits to monitor trends, only the current average yield. ) Due to the inherent difference in lot sizes, I find it too confusing to try to recalculate the UCL and LCL for each lot / day. 

Hope this helps,

Ed Cosper


----------
From:  Dave Willhard[SMTP:[log in to unmask]]
Sent:  Thursday, March 27, 1997 5:42 PM
To:  [log in to unmask]
Subject:  SPC chart for % defective

Dr. Donald Wheeler in several of his "SPC Toolkit" columns in Quality Digest has
seemed to suggest that Individual X / Moving Range control charts can be
used to control attribute data such as percentage defective, first
pass yield, etc.  Most SPC textbooks only list standard attribute
charts (P, C, etc.) when discussing that type of data.

Does anyone currently use a "variables" type chart to control attribute
data?  I would like to use an X/MR chart rather than a P chart for % defective because
it's easier for operators to plot.  I'm just wondering if it's really
valid.  Dr. Wheeler gives examples of X/MR charts used for this type
of data but never really explains the concept of why it is valid to use
them rather than standard attribute charts.

Dave Hall
Quality Engineer
Compeq International
<[log in to unmask]>

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