Monte Carlo Simulations for probabilistic validation of consequence reasoning from Multilevel Flow Modelling

Emil K. Nielsen; Denis Kirchhübel; Thomas Martini Jørgensen

doi:10.1109/ETFA46521.2020.9212179

Monte Carlo Simulations for probabilistic validation of consequence reasoning from Multilevel Flow Modelling

Emil K. Nielsen, Denis Kirchhübel, Thomas Martini Jørgensen

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

Multilevel Flow Modelling can be used to identify causes or consequences of anomalies in process systems. The models can be used to identify numerous possible propagations of causes or effects but cannot distinguish between likely and unlikely causes or effects. We present a method for identifying likely and unlikely effect propagations in a given process window from Monte Carlo Simulations. We show that the joint probability of effects can be used to determine the probability of individual propagation paths. The analysis allows to identify subsets of the process window where certain effect propagations are more likely. The method enables prompt identification of likely propagations of effects from process anomalies.

Original language	English
Title of host publication	Proceedings of 25^th IEEE International Conference on Emerging Technologies and Factory Automation
Volume	1
Publisher	IEEE
Publication date	2020
Pages	1351-1354
ISBN (Print)	9781728189567
DOIs	https://doi.org/10.1109/ETFA46521.2020.9212179
Publication status	Published - 2020
Event	25th IEEE International Conference on Emerging Technologies and Factory Automation - Virtual event, Vienna, Austria Duration: 8 Sept 2020 → 11 Sept 2020 http://www.ieee-etfa.org/2020/

Conference

Conference	25th IEEE International Conference on Emerging Technologies and Factory Automation
Location	Virtual event
Country/Territory	Austria
City	Vienna
Period	08/09/2020 → 11/09/2020
Internet address	http://www.ieee-etfa.org/2020/

Series	Emerging Technologies and Factory Automation (etfa), International Conference on
ISSN	1946-0759

Keywords

Functional Modelling
Multilevel Flow Modelling
Consequence prediction
Monte Carlo Simulations

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10.1109/ETFA46521.2020.9212179

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Nielsen, Emil K. ; Kirchhübel, Denis ; Jørgensen, Thomas Martini. / Monte Carlo Simulations for probabilistic validation of consequence reasoning from Multilevel Flow Modelling. Proceedings of 25^th IEEE International Conference on Emerging Technologies and Factory Automation. Vol. 1 IEEE, 2020. pp. 1351-1354 (Emerging Technologies and Factory Automation (etfa), International Conference on).

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abstract = "Multilevel Flow Modelling can be used to identify causes or consequences of anomalies in process systems. The models can be used to identify numerous possible propagations of causes or effects but cannot distinguish between likely and unlikely causes or effects. We present a method for identifying likely and unlikely effect propagations in a given process window from Monte Carlo Simulations. We show that the joint probability of effects can be used to determine the probability of individual propagation paths. The analysis allows to identify subsets of the process window where certain effect propagations are more likely. The method enables prompt identification of likely propagations of effects from process anomalies.",

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publisher = "IEEE",

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note = "25th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2020 ; Conference date: 08-09-2020 Through 11-09-2020",

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Nielsen, EK, Kirchhübel, D & Jørgensen, TM 2020, Monte Carlo Simulations for probabilistic validation of consequence reasoning from Multilevel Flow Modelling. in Proceedings of 25^th IEEE International Conference on Emerging Technologies and Factory Automation. vol. 1, IEEE, Emerging Technologies and Factory Automation (etfa), International Conference on, pp. 1351-1354, 25th IEEE International Conference on Emerging Technologies and Factory Automation, Vienna, Austria, 08/09/2020. https://doi.org/10.1109/ETFA46521.2020.9212179

Monte Carlo Simulations for probabilistic validation of consequence reasoning from Multilevel Flow Modelling. / Nielsen, Emil K.; Kirchhübel, Denis; Jørgensen, Thomas Martini.
Proceedings of 25^th IEEE International Conference on Emerging Technologies and Factory Automation. Vol. 1 IEEE, 2020. p. 1351-1354 (Emerging Technologies and Factory Automation (etfa), International Conference on).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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AU - Jørgensen, Thomas Martini

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N2 - Multilevel Flow Modelling can be used to identify causes or consequences of anomalies in process systems. The models can be used to identify numerous possible propagations of causes or effects but cannot distinguish between likely and unlikely causes or effects. We present a method for identifying likely and unlikely effect propagations in a given process window from Monte Carlo Simulations. We show that the joint probability of effects can be used to determine the probability of individual propagation paths. The analysis allows to identify subsets of the process window where certain effect propagations are more likely. The method enables prompt identification of likely propagations of effects from process anomalies.

AB - Multilevel Flow Modelling can be used to identify causes or consequences of anomalies in process systems. The models can be used to identify numerous possible propagations of causes or effects but cannot distinguish between likely and unlikely causes or effects. We present a method for identifying likely and unlikely effect propagations in a given process window from Monte Carlo Simulations. We show that the joint probability of effects can be used to determine the probability of individual propagation paths. The analysis allows to identify subsets of the process window where certain effect propagations are more likely. The method enables prompt identification of likely propagations of effects from process anomalies.

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KW - Consequence prediction

KW - Monte Carlo Simulations

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T3 - Emerging Technologies and Factory Automation (etfa), International Conference on

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BT - Proceedings of 25th IEEE International Conference on Emerging Technologies and Factory Automation

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ER -

Nielsen EK, Kirchhübel D, Jørgensen TM. Monte Carlo Simulations for probabilistic validation of consequence reasoning from Multilevel Flow Modelling. In Proceedings of 25^th IEEE International Conference on Emerging Technologies and Factory Automation. Vol. 1. IEEE. 2020. p. 1351-1354. (Emerging Technologies and Factory Automation (etfa), International Conference on). doi: 10.1109/ETFA46521.2020.9212179

Monte Carlo Simulations for probabilistic validation of consequence reasoning from Multilevel Flow Modelling

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