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Spatio-temporal modelling of corrosion in an industrial furnace

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Spatio-temporal modelling of corrosion in an industrial furnace. / Little, J.; Goldstein, M.; Jonathan, P. et al.
In: Applied Stochastic Models in Business and Industry, Vol. 20, No. 3, 2004, p. 219-238.

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

Harvard

Little, J, Goldstein, M, Jonathan, P & Den Heijer, K 2004, 'Spatio-temporal modelling of corrosion in an industrial furnace', Applied Stochastic Models in Business and Industry, vol. 20, no. 3, pp. 219-238. https://doi.org/10.1002/asmb.524

APA

Little, J., Goldstein, M., Jonathan, P., & Den Heijer, K. (2004). Spatio-temporal modelling of corrosion in an industrial furnace. Applied Stochastic Models in Business and Industry, 20(3), 219-238. https://doi.org/10.1002/asmb.524

Vancouver

Little J, Goldstein M, Jonathan P, Den Heijer K. Spatio-temporal modelling of corrosion in an industrial furnace. Applied Stochastic Models in Business and Industry. 2004;20(3):219-238. doi: 10.1002/asmb.524

Author

Little, J. ; Goldstein, M. ; Jonathan, P. et al. / Spatio-temporal modelling of corrosion in an industrial furnace. In: Applied Stochastic Models in Business and Industry. 2004 ; Vol. 20, No. 3. pp. 219-238.

Bibtex

@article{6d01adbfb6994efa9aa290e0c350a40c,
title = "Spatio-temporal modelling of corrosion in an industrial furnace",
abstract = "Optimal inspection and maintenance of complex systems in modern industry is important for safety and economic reasons. With appropriate statistical modelling, the utilization of inspection resources and quality of inferences can be greatly improved. Modelling and inspection of a full-scale industrial furnace subject to corrosion will be considered. A suitable Bayesian spatio-temporal dynamic linear model is developed for wall thickness, by eliciting the beliefs of experts and incorporating other relevant data for related systems. The model may be used to derive efficient inspection schedules for corrosion detection and we demonstrate the considerable reduction in the inspection burden which the model allows. Copyright {\textcopyright} 2004 John Wiley & Sons, Ltd.",
keywords = "Correlation, Corrosion, DLM, Inspection, Simulation, Spatio-temporal, Computational methods, Industrial furnaces, Risks, Statistical methods, Corrosion rate, Dynamic linear model (DLM), Spatio-temporal modeling, Time series model",
author = "J. Little and M. Goldstein and P. Jonathan and {Den Heijer}, K.",
year = "2004",
doi = "10.1002/asmb.524",
language = "English",
volume = "20",
pages = "219--238",
journal = "Applied Stochastic Models in Business and Industry",
issn = "1524-1904",
publisher = "John Wiley and Sons Ltd",
number = "3",

}

RIS

TY - JOUR

T1 - Spatio-temporal modelling of corrosion in an industrial furnace

AU - Little, J.

AU - Goldstein, M.

AU - Jonathan, P.

AU - Den Heijer, K.

PY - 2004

Y1 - 2004

N2 - Optimal inspection and maintenance of complex systems in modern industry is important for safety and economic reasons. With appropriate statistical modelling, the utilization of inspection resources and quality of inferences can be greatly improved. Modelling and inspection of a full-scale industrial furnace subject to corrosion will be considered. A suitable Bayesian spatio-temporal dynamic linear model is developed for wall thickness, by eliciting the beliefs of experts and incorporating other relevant data for related systems. The model may be used to derive efficient inspection schedules for corrosion detection and we demonstrate the considerable reduction in the inspection burden which the model allows. Copyright © 2004 John Wiley & Sons, Ltd.

AB - Optimal inspection and maintenance of complex systems in modern industry is important for safety and economic reasons. With appropriate statistical modelling, the utilization of inspection resources and quality of inferences can be greatly improved. Modelling and inspection of a full-scale industrial furnace subject to corrosion will be considered. A suitable Bayesian spatio-temporal dynamic linear model is developed for wall thickness, by eliciting the beliefs of experts and incorporating other relevant data for related systems. The model may be used to derive efficient inspection schedules for corrosion detection and we demonstrate the considerable reduction in the inspection burden which the model allows. Copyright © 2004 John Wiley & Sons, Ltd.

KW - Correlation

KW - Corrosion

KW - DLM

KW - Inspection

KW - Simulation

KW - Spatio-temporal

KW - Computational methods

KW - Industrial furnaces

KW - Risks

KW - Statistical methods

KW - Corrosion rate

KW - Dynamic linear model (DLM)

KW - Spatio-temporal modeling

KW - Time series model

U2 - 10.1002/asmb.524

DO - 10.1002/asmb.524

M3 - Journal article

VL - 20

SP - 219

EP - 238

JO - Applied Stochastic Models in Business and Industry

JF - Applied Stochastic Models in Business and Industry

SN - 1524-1904

IS - 3

ER -