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Abstract
Cause-selecting control charts use incoming quality measurements and out-going quality measurements in an attempt to distinguish between in-coming quality problems and problems in the current operation of a manufacturing process. We examine the assumptions underlying this useful type of chart and its relationship with the multivariate T2 chart. We propose using prediction limits with cause-selecting charts to improve their statistical performance.
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Notes on contributors
Mark R. Wade
Dr. Wade is a graduate of the Applied Statistics Program. He is a Member of ASQC.
William H. Woodall
Dr. Woodall is a Professor in the Department of Management Science and Statistics. He is a Senior Member of ASQC.