A model-based approach to quality control of paper production.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Published

Standard

A model-based approach to quality control of paper production. / Brown, P. E.; Diggle, Peter J.; Henderson, R.
In: Applied Stochastic Models in Business and Industry, Vol. 20, No. 3, 2004, p. 173-184.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Brown, PE, Diggle, PJ & Henderson, R 2004, 'A model-based approach to quality control of paper production.', Applied Stochastic Models in Business and Industry, vol. 20, no. 3, pp. 173-184. https://doi.org/10.1002/asmb.526

APA

Brown, P. E., Diggle, P. J., & Henderson, R. (2004). A model-based approach to quality control of paper production. Applied Stochastic Models in Business and Industry, 20(3), 173-184. https://doi.org/10.1002/asmb.526

Vancouver

Brown PE, Diggle PJ, Henderson R. A model-based approach to quality control of paper production. Applied Stochastic Models in Business and Industry. 2004;20(3):173-184. doi: 10.1002/asmb.526

Author

Brown, P. E. ; Diggle, Peter J. ; Henderson, R. / A model-based approach to quality control of paper production. In: Applied Stochastic Models in Business and Industry. 2004 ; Vol. 20, No. 3. pp. 173-184.

Bibtex

@article{f254cd4f619c4d05aa8fe643833e3694,

title = "A model-based approach to quality control of paper production.",

abstract = "Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis ) was first published in 1985 publishing contributions in the interface between stochastic modelling data analysis and their applications in business finance insurance management and production. The main objective is to publish papers both technical and practical presenting new results which solve real-life problems or have great potential in doing so. A second objective is to present new methods for solving such problems i.e. optimization data base management knowledge acquisition expert systems computer-aided decision supports and neural computing. The scope of the journal is now broadened both in supporting topics and in appropriate methodology. Topics to be added include managerial processes reliability quality control data analysis and data mining. New methodologies include wavelets Markov-chain Monte Carlo methods and spatial statistics.",

keywords = "state space model • information matrix • multivariate control charts",

author = "Brown, {P. E.} and Diggle, {Peter J.} and R. Henderson",

year = "2004",

doi = "10.1002/asmb.526",

language = "English",

volume = "20",

pages = "173--184",

journal = "Applied Stochastic Models in Business and Industry",

issn = "1526-4025",

publisher = "John Wiley and Sons Ltd",

number = "3",

}

RIS

TY - JOUR

T1 - A model-based approach to quality control of paper production.

AU - Brown, P. E.

AU - Diggle, Peter J.

AU - Henderson, R.

PY - 2004

Y1 - 2004

N2 - Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis ) was first published in 1985 publishing contributions in the interface between stochastic modelling data analysis and their applications in business finance insurance management and production. The main objective is to publish papers both technical and practical presenting new results which solve real-life problems or have great potential in doing so. A second objective is to present new methods for solving such problems i.e. optimization data base management knowledge acquisition expert systems computer-aided decision supports and neural computing. The scope of the journal is now broadened both in supporting topics and in appropriate methodology. Topics to be added include managerial processes reliability quality control data analysis and data mining. New methodologies include wavelets Markov-chain Monte Carlo methods and spatial statistics.

AB - Applied Stochastic Models in Business and Industry (formerly Applied Stochastic Models and Data Analysis ) was first published in 1985 publishing contributions in the interface between stochastic modelling data analysis and their applications in business finance insurance management and production. The main objective is to publish papers both technical and practical presenting new results which solve real-life problems or have great potential in doing so. A second objective is to present new methods for solving such problems i.e. optimization data base management knowledge acquisition expert systems computer-aided decision supports and neural computing. The scope of the journal is now broadened both in supporting topics and in appropriate methodology. Topics to be added include managerial processes reliability quality control data analysis and data mining. New methodologies include wavelets Markov-chain Monte Carlo methods and spatial statistics.

KW - state space model • information matrix • multivariate control charts

U2 - 10.1002/asmb.526

DO - 10.1002/asmb.526

M3 - Journal article

VL - 20

SP - 173

EP - 184

JO - Applied Stochastic Models in Business and Industry

JF - Applied Stochastic Models in Business and Industry

SN - 1526-4025

IS - 3

ER -

Research

Links

Text available via DOI:

Keywords