A model-based approach to quality control of paper production

Patrick E. Brown, Peter J. Diggle, Robin Henderson

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)173-184
Number of pages12
JournalApplied Stochastic Models in Business and Industry
Issue number3
StatePublished - Jul 2004
Externally publishedYes


  • Information matrix
  • Multivariate control charts
  • State space model

ASJC Scopus subject areas

  • Applied Mathematics
  • Statistics and Probability
  • Management Science and Operations Research


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