Abstract
Principal component analysis (PCA) performed on data from pilot scale chemimechanical (CMP) pulping trials indicates that over 90% of the variation in 11 handsheet properties can be expressed in terms of only 4 composite variables. The relaionships between the original properties and the new composite properties are displayed graphically using a biplot of the PCA scores. These techniques are combined to construct a chart capable of monitoring changes in a large number of quality responses simultaneously. Model accuracy can be monitored on the same chart resulting in a tool which will self-diagnose as well as offer a powerful overview of the process.
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