Toward Comprehensive Decision Support Using Multilevel Flow Modeling

Research output: Contribution to journalJournal articleResearchpeer-review

38 Downloads (Pure)

Abstract

The complexity of modern industrial plants poses significant challenges for the design of effective operator interfaces. Although established practices can significantly reduce the frequency of alarms, operators often cannot resolve the failure cascades commonly occurring during emergency situations. Automating control rooms by incorporating design and operation knowledge about the systems can significantly improve operator efficacy. Intelligent support systems should reduce the amount of information and provide more context to the operators. The operators focus should be shifted from information acquisition to taking informed decisions about mitigation steps. This contribution gives a brief review of the development of Multilevel Flow Modeling (MFM) and its application to provide operators with decision support and situation awareness, focusing on implementations directly utilising the knowledge represented in MFM. Finally, current efforts toward a comprehensive intelligent human machine interface for operators are outlined.
Original languageEnglish
Book seriesIFAC-PapersOnLine
Volume52
Issue number11
Pages (from-to)31-36
ISSN2405-8963
DOIs
Publication statusPublished - 2019
Event5th IFAC Conference on Intelligent Control and Automation Sciences - Riddel Hall, Belfast, United Kingdom
Duration: 21 Aug 201923 Aug 2019
http://www.qub.ac.uk/sites/icons2019/

Conference

Conference5th IFAC Conference on Intelligent Control and Automation Sciences
LocationRiddel Hall
CountryUnited Kingdom
CityBelfast
Period21/08/201923/08/2019
Internet address

Keywords

  • Human supervisory control
  • Decision support systems
  • Intelligent knowledge-based systems
  • Alarm systems
  • Reasoning
  • Fault diagnosis

Cite this

@article{d8406e5247544d78971912b67626ae04,
title = "Toward Comprehensive Decision Support Using Multilevel Flow Modeling",
abstract = "The complexity of modern industrial plants poses significant challenges for the design of effective operator interfaces. Although established practices can significantly reduce the frequency of alarms, operators often cannot resolve the failure cascades commonly occurring during emergency situations. Automating control rooms by incorporating design and operation knowledge about the systems can significantly improve operator efficacy. Intelligent support systems should reduce the amount of information and provide more context to the operators. The operators focus should be shifted from information acquisition to taking informed decisions about mitigation steps. This contribution gives a brief review of the development of Multilevel Flow Modeling (MFM) and its application to provide operators with decision support and situation awareness, focusing on implementations directly utilising the knowledge represented in MFM. Finally, current efforts toward a comprehensive intelligent human machine interface for operators are outlined.",
keywords = "Human supervisory control, Decision support systems, Intelligent knowledge-based systems, Alarm systems, Reasoning, Fault diagnosis",
author = "Denis Kirchh{\"u}bel and Morten Lind and Ole Ravn",
year = "2019",
doi = "10.1016/j.ifacol.2019.09.114",
language = "English",
volume = "52",
pages = "31--36",
journal = "IFAC-PapersOnLine",
issn = "2405-8963",
publisher = "Elsevier",
number = "11",

}

Toward Comprehensive Decision Support Using Multilevel Flow Modeling. / Kirchhübel, Denis; Lind, Morten; Ravn, Ole.

In: IFAC-PapersOnLine, Vol. 52, No. 11, 2019, p. 31-36.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Toward Comprehensive Decision Support Using Multilevel Flow Modeling

AU - Kirchhübel, Denis

AU - Lind, Morten

AU - Ravn, Ole

PY - 2019

Y1 - 2019

N2 - The complexity of modern industrial plants poses significant challenges for the design of effective operator interfaces. Although established practices can significantly reduce the frequency of alarms, operators often cannot resolve the failure cascades commonly occurring during emergency situations. Automating control rooms by incorporating design and operation knowledge about the systems can significantly improve operator efficacy. Intelligent support systems should reduce the amount of information and provide more context to the operators. The operators focus should be shifted from information acquisition to taking informed decisions about mitigation steps. This contribution gives a brief review of the development of Multilevel Flow Modeling (MFM) and its application to provide operators with decision support and situation awareness, focusing on implementations directly utilising the knowledge represented in MFM. Finally, current efforts toward a comprehensive intelligent human machine interface for operators are outlined.

AB - The complexity of modern industrial plants poses significant challenges for the design of effective operator interfaces. Although established practices can significantly reduce the frequency of alarms, operators often cannot resolve the failure cascades commonly occurring during emergency situations. Automating control rooms by incorporating design and operation knowledge about the systems can significantly improve operator efficacy. Intelligent support systems should reduce the amount of information and provide more context to the operators. The operators focus should be shifted from information acquisition to taking informed decisions about mitigation steps. This contribution gives a brief review of the development of Multilevel Flow Modeling (MFM) and its application to provide operators with decision support and situation awareness, focusing on implementations directly utilising the knowledge represented in MFM. Finally, current efforts toward a comprehensive intelligent human machine interface for operators are outlined.

KW - Human supervisory control

KW - Decision support systems

KW - Intelligent knowledge-based systems

KW - Alarm systems

KW - Reasoning

KW - Fault diagnosis

U2 - 10.1016/j.ifacol.2019.09.114

DO - 10.1016/j.ifacol.2019.09.114

M3 - Journal article

VL - 52

SP - 31

EP - 36

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

SN - 2405-8963

IS - 11

ER -