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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2282/754
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| Title: | Informative score-loading-contribution plots for multi-response process monitoring |
| Authors: | Ergon, Rolf |
| Issue Date: | 2009 |
| Publishers version: | http://dx.doi.org/10.1016/j.chemolab.2008.08.001 |
| Abstract: | The projection based multivariate data methods of principal component regression (PCR) and
partial least squares regression (PLSR) are well established in the eld of process monitoring. Use
of score and loading plots for visualization is, however, complicated when many components are
required for good predictions, and the information is therefore often compressed into less informative
T2 and contribution plots. The score information may, however, be further compressed by projection
onto subspaces spanned by the vectors of prediction coe¢ cients for the response variables. This is
especially attractive in the case of two response variables, i.e. when the model reduction results in
a single score-loading biplot. Contribution vectors for the process variables, as well as a con dence
ellipse, may also be included in such a plot. As illustrated in an industrial data example, such a
score-loading-contribution plot provides means of both failure detection and fault diagnosis. |
| Keywords: | Process monitoring
Model reduction
Score-loading-contribution plots |
| Publisher: | Elsevier |
| Document type: | Journal article |
| URI: | http://hdl.handle.net/2282/754 |
| Appears in Collections: | Institutt for elektro, IT og kybernetikk
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