Abstract
The techniques of principal component analysis (PCA) and partial least squares (PLS) are introduced from the point of view of providing a multivariate statistical method for modelling process plants. The advantages and limitations of PCA and PLS are discussed from the perspective of the type of data and problems that might be encountered in this application area. These concepts are exemplified by two case studies dealing first with data from a continuous stirred tank reactor (CSTR) simulation and second a literature source describing a low-density polyethylene (LDPE) reactor simulation.
| Original language | English |
|---|---|
| Pages (from-to) | 749-754 |
| Number of pages | 6 |
| Journal | Analyst |
| Volume | 121 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Jun 1996 |
| Externally published | Yes |
Keywords
- Partial least squares
- Principal component analysis
- Statistical process control
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