A model-based approach to quality control of paper production: Research Articles

  • Authors:

  • Patrick E. Brown;Peter J. Diggle;Robin Henderson

  • Affiliations:

  • Department of Mathematics and Statistics, Lancaster University, Lancaster LA1 4YF, U.K.;Department of Mathematics and Statistics, Lancaster University, Lancaster LA1 4YF, U.K.;Department of Mathematics and Statistics, Lancaster University, Lancaster LA1 4YF, U.K.

  • Venue:
  • Applied Stochastic Models in Business and Industry - Innovative Statistical Models in the European Business and Industry
  • Year:
  • 2004

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Abstract

This paper uses estimated model parameters as inputs into multivariate quality control charts. The thickness of paper leaving a paper mill is measured at a high sampling rate, and these data are grouped into successive data segments. A stochastic model for paper is fitted to each data segment, leading to parameter estimates and information-based standard errors for these estimates. The estimated model parameters vary by more than one can be explained by the information-based standard errors, suggesting that the ‘true’ underlying parameters are not constant over time. A model is formulated for the true parameters in which the information matrix dictates the distribution for the observed parameters given the true parameters. Copyright © 2004 John Wiley & Sons, Ltd.