Abstract: U charts are used for count data following the Poisson distribution. However, the U chart has symmetrical control limits when the Poisson distribution is nonsymmetrical. As a result, the upper control limit can have a rate of false detection as high as 1 in 11.5 points plotted. This can result in wasted resources investigating […]
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Abstract: The only commonly used control chart that cannot be normalized is the Individuals (I) chart. A procedure called a Normalized Individuals (IN) chart is provided for normalizing data associated with an I chart. The IN chart works nearly identical to the Laney U’ and P’ charts for count data. The IN chart has certain theoretical advantages as
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Abstract: P charts are used for count data following the Binomial distribution. However, the P chart has symmetrical control limits when the Binomial distribution is nonsymmetrical. As a result, the upper control limit can have a rate of false detection as high as 1 in 11.5 points plotted. This can result in wasted resources investigating
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DR. WAYNE A. TAYLORTaylor Enterprises, Inc., Libertyville, IL 60048 Change-point analysis is a powerful new tool for determining whether a change has taken place. It is capable of detecting subtle changes missed by control charts. Further, it better characterizes the changes detected by providing confidence levels and confidence intervals. When collecting online data, a change-point analysis is not
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WAYNE A. TAYLORBaxter Healthcare Corporation, Round Lake, IL 60073 Change-point analysis is a powerful new tool for determining whether a change has taken place. It is capable of detecting subtle changes missed by control charts. Further, it better characterizes the changes detected by providing confidence levels and confidence intervals. When collecting online data, a change-point
Change-Point Analysis: A Powerful New Tool For Detecting Changes Read More »
WAYNE A. TAYLORBaxter Healthcare Corporation, Round Lake, IL 60073 Statistical methods such as control charts and change-point analysis are commonly usedto determine whether the mean has shifted. Such methods assume independent errorsaround a possibly changing mean. When such techniques are applied to autoregressivedata, erroneous conclusions can result. However, shifts of the mean createautocorrelation between the
A Pattern Test for Distinguishing Between Autoregressive and Mean-Shift Data Read More »
Dr. Wayne A. Taylor The use of SPC is preferable to relying on acceptance sampling. It is better to make defect-free product than to sort out the defects later. However, with attribute data, care must be taken in implementing SPC to avoid only an illusion of change. Suppose a packing operation inspects for missing parts
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