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Statistical models for on-line monitoring of cardboard quality properties

Nordström, Fredrik LU ; Lindström, Torgny LU and Holst, Jan LU (2005) In Preprint without journal information
Abstract
A statistical study of data containing observations of process and quality variables from the SCA paper mill in Munksund, Sweden, is presented. The emphasis in this analysis has been on modelling the laboratory collected paper quality variables by means of the data available on-line, during production.

The primary tool for prediction, or estimation at non observed time instants, of variables was partial least squares (PLS). In this analysis, good prediction results were obtained for the laboratory measured paper quality variables. Thus by these results, process and quality variables obtained during production can be used on-line to achieve good estimates of the important quality variables that otherwise only can be obtained... (More)
A statistical study of data containing observations of process and quality variables from the SCA paper mill in Munksund, Sweden, is presented. The emphasis in this analysis has been on modelling the laboratory collected paper quality variables by means of the data available on-line, during production.

The primary tool for prediction, or estimation at non observed time instants, of variables was partial least squares (PLS). In this analysis, good prediction results were obtained for the laboratory measured paper quality variables. Thus by these results, process and quality variables obtained during production can be used on-line to achieve good estimates of the important quality variables that otherwise only can be obtained off-line. Another important result obtained from the PLS analysis was the relative importance of the variables used for estimation. From these results the most important variables for quality control, with respect to the paper quality variables, could be identified.

It was shown that the temporal correlations within the variables were generally quite strong. In order to model this dependency in time, stochastic differential equations were utilized. These models were found to successfully explain the correlations in the data such that the resulting residuals were nearly independent.

Further, the possibility for on-line modelling of the paper tensile properties were investigated. More precisely, using on-line predictions of the tensile strength, the tensile stiffness and the elongation, on-line prediction of the stress vs strain curves were conducted. No data for verification of these results were available from the Munksund paper mill, therefore another set of laboratory data were utilized for this purpose. Good results were achieved by fitting a parametric model to the tensile variables, in that the estimated stress vs strain curves showed good agreement with the measured values. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
unpublished
subject
in
Preprint without journal information
issue
2005:24
publisher
Manne Siegbahn Institute
ISSN
0348-7911
language
English
LU publication?
yes
id
560f4efe-d96e-477c-a7a3-4bda6e1d9745 (old id 930224)
date added to LUP
2008-01-15 15:22:13
date last changed
2016-04-16 07:05:52
@misc{560f4efe-d96e-477c-a7a3-4bda6e1d9745,
  abstract     = {A statistical study of data containing observations of process and quality variables from the SCA paper mill in Munksund, Sweden, is presented. The emphasis in this analysis has been on modelling the laboratory collected paper quality variables by means of the data available on-line, during production. <br/><br>
The primary tool for prediction, or estimation at non observed time instants, of variables was partial least squares (PLS). In this analysis, good prediction results were obtained for the laboratory measured paper quality variables. Thus by these results, process and quality variables obtained during production can be used on-line to achieve good estimates of the important quality variables that otherwise only can be obtained off-line. Another important result obtained from the PLS analysis was the relative importance of the variables used for estimation. From these results the most important variables for quality control, with respect to the paper quality variables, could be identified. <br/><br>
It was shown that the temporal correlations within the variables were generally quite strong. In order to model this dependency in time, stochastic differential equations were utilized. These models were found to successfully explain the correlations in the data such that the resulting residuals were nearly independent. <br/><br>
Further, the possibility for on-line modelling of the paper tensile properties were investigated. More precisely, using on-line predictions of the tensile strength, the tensile stiffness and the elongation, on-line prediction of the stress vs strain curves were conducted. No data for verification of these results were available from the Munksund paper mill, therefore another set of laboratory data were utilized for this purpose. Good results were achieved by fitting a parametric model to the tensile variables, in that the estimated stress vs strain curves showed good agreement with the measured values.},
  author       = {Nordström, Fredrik and Lindström, Torgny and Holst, Jan},
  issn         = {0348-7911},
  language     = {eng},
  number       = {2005:24},
  publisher    = {ARRAY(0xa2ceef0)},
  series       = {Preprint without journal information},
  title        = {Statistical models for on-line monitoring of cardboard quality properties},
  year         = {2005},
}