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A method for multiblock statistical process control is described, involving the computation of Q and D statistics both for individual blocks and for the overall process using window consensus principal components analysis (WCPCA). The approach overcomes two common problems. The first is a small normal operating conditions (NOC) region, which is done by determining the Q‐statistic limits and D statistics...
In process monitoring, a representative out‐of‐control class of samples cannot be generated. Here, it is assumed that it is possible to obtain a representative subset of samples from a single ‘in‐control class’ and one class classifiers namely Q and D statistics (respectively the residual distance to the disjoint PC model and the Mahalanobis distance to the centre of the QDA model in the projected...
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