Multivariate process monitoring of a newsprint mill. Application to modelling and predicting COD load resulting from de‐inking of recycled paper

Multivariate process monitoring was applied to understand the influence of numerous production parameters on the release of organic matter into the effluent of a newsprint mill. The release was characterized by measuring the chemical oxygen demand (COD). The relationships between over 50 process variables and the COD load were investigated using PLS regression and time series analysis. The results showed that variations in COD could be predicted accurately. Furthermore, model interpretation identified the most influential process parameters. Copyright © 2001 John Wiley & Sons, Ltd.

[1]  H. Martens,et al.  Modified Jack-knife estimation of parameter uncertainty in bilinear modelling by partial least squares regression (PLSR) , 2000 .

[2]  Theodora Kourti,et al.  Statistical Process Control of Multivariate Processes , 1994 .

[3]  Harald Martens,et al.  REVIEW OF PARTIAL LEAST SQUARES REGRESSION PREDICTION ERROR IN UNSCRAMBLER , 1998 .

[4]  I. Wakeling,et al.  A test of significance for partial least squares regression , 1993 .

[5]  S. D. Jong,et al.  Multivariate statistical process control in chromatography , 1997 .

[6]  Erik Johansson,et al.  Multivariate process and quality monitoring applied to an electrolysis process: Part I. Process supervision with multivariate control charts , 1998 .

[7]  Lars Renberg,et al.  Non‐linear modelling with a coupled neural network — PLS regression system , 1996 .

[8]  Bjørn K. Alsberg,et al.  Parsimonious multiscale classification models , 2000 .

[9]  Age K. Smilde.  Comments on three‐way analyses used for batch process data , 2001 .

[10]  Pekka Teppola,et al.  Kalman filter for updating the coefficients of regression models. A case study from an activated sludge waste-water treatment plant , 1999 .

[11]  P. Minkkinen,et al.  A combined approach of partial least squares and fuzzy c-means clustering for the monitoring of an activated-sludge waste-water treatment plant , 1998 .

[12]  Pierre Dardenne,et al.  Validation and verification of regression in small data sets , 1998 .

[13]  Bhavik R. Bakshi,et al.  Multiscale analysis and modeling using wavelets , 1999 .

[14]  S. Wold.  Cross-Validatory Estimation of the Number of Components in Factor and Principal Components Models , 1978 .

[15]  Torbjörn Lundstedt,et al.  PREPROCESSING PEPTIDE SEQUENCES FOR MULTIVARIATE SEQUENCE-PROPERTY ANALYSIS , 1998 .

[16]  Harald Martens,et al.  A multivariate calibration problem in analytical chemistry solved by partial least-squares models in latent variables , 1983 .

[17]  Michael J. Piovoso,et al.  PCA of Wavelet Transformed Process Data for Monitoring , 1997, Intell. Data Anal..

[18]  Matthew Clark,et al.  The Probability of Chance Correlation Using Partial Least Squares (PLS) , 1993 .

[19]  Theodora Kourti,et al.  Comparing alternative approaches for multivariate statistical analysis of batch process data , 1999 .