Computing dependent industrial alarms for alarm flood reduction

Jens Folmer; Birgit Vogel-Heuser

doi:10.1109/SSD.2012.6198008

Computing dependent industrial alarms for alarm flood reduction

Jens Folmer
, Birgit Vogel-Heuser

Chair of Automation and Information Systems

Technical University of Munich

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

44 Scopus citations

Abstract

In the domain of process control, operators face the problem that more alarms are generated than can be physically addressed by a single operator. Such a situation is called alarm flood. The reasons for alarm floods are either badly designed alarm management systems (AMS) or causal dependent disturbances which either way, raise an alarm based on a single causal disturbance. These dependencies are difficult to recognize during the engineering of an AMS. This article presents an overview of an algorithm for the automatic alarm data analyzer (AADA). It is able to find possible and significant reasons for alarm floods by identifying the most frequent alarms and those causal alarms consolidating alarm-sequences. They are to be used to improve and to redesign an AMS, so that the alarm flood problem can be reduced at the end.

Original language	English
Title of host publication	International Multi-Conference on Systems, Signals and Devices, SSD 2012 - Summary Proceedings
DOIs	https://doi.org/10.1109/SSD.2012.6198008
State	Published - 2012
Event	9th International Multi-Conference on Systems, Signals and Devices, SSD 2012 - Chemnitz, Germany Duration: 20 Mar 2012 → 23 Mar 2012

Publication series

Name	International Multi-Conference on Systems, Signals and Devices, SSD 2012 - Summary Proceedings

Conference

Conference	9th International Multi-Conference on Systems, Signals and Devices, SSD 2012
Country/Territory	Germany
City	Chemnitz
Period	20/03/12 → 23/03/12

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

Alarm Floods
Alarm Management
Manufacturing
Process Control
Re-Engineering

Access to Document

10.1109/SSD.2012.6198008

Cite this

@inproceedings{0de4e77560454816b4035e19cc1b8d93,

title = "Computing dependent industrial alarms for alarm flood reduction",

abstract = "In the domain of process control, operators face the problem that more alarms are generated than can be physically addressed by a single operator. Such a situation is called alarm flood. The reasons for alarm floods are either badly designed alarm management systems (AMS) or causal dependent disturbances which either way, raise an alarm based on a single causal disturbance. These dependencies are difficult to recognize during the engineering of an AMS. This article presents an overview of an algorithm for the automatic alarm data analyzer (AADA). It is able to find possible and significant reasons for alarm floods by identifying the most frequent alarms and those causal alarms consolidating alarm-sequences. They are to be used to improve and to redesign an AMS, so that the alarm flood problem can be reduced at the end.",

keywords = "Alarm Floods, Alarm Management, Manufacturing, Process Control, Re-Engineering",

author = "Jens Folmer and Birgit Vogel-Heuser",

year = "2012",

doi = "10.1109/SSD.2012.6198008",

language = "English",

isbn = "9781467315906",

series = "International Multi-Conference on Systems, Signals and Devices, SSD 2012 - Summary Proceedings",

booktitle = "International Multi-Conference on Systems, Signals and Devices, SSD 2012 - Summary Proceedings",

note = "9th International Multi-Conference on Systems, Signals and Devices, SSD 2012 ; Conference date: 20-03-2012 Through 23-03-2012",

}

Folmer, J & Vogel-Heuser, B 2012, Computing dependent industrial alarms for alarm flood reduction. in International Multi-Conference on Systems, Signals and Devices, SSD 2012 - Summary Proceedings., 6198008, International Multi-Conference on Systems, Signals and Devices, SSD 2012 - Summary Proceedings, 9th International Multi-Conference on Systems, Signals and Devices, SSD 2012, Chemnitz, Germany, 20/03/12. https://doi.org/10.1109/SSD.2012.6198008

Computing dependent industrial alarms for alarm flood reduction. / Folmer, Jens; Vogel-Heuser, Birgit.
International Multi-Conference on Systems, Signals and Devices, SSD 2012 - Summary Proceedings. 2012. 6198008 (International Multi-Conference on Systems, Signals and Devices, SSD 2012 - Summary Proceedings).

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

TY - GEN

T1 - Computing dependent industrial alarms for alarm flood reduction

AU - Folmer, Jens

AU - Vogel-Heuser, Birgit

PY - 2012

Y1 - 2012

N2 - In the domain of process control, operators face the problem that more alarms are generated than can be physically addressed by a single operator. Such a situation is called alarm flood. The reasons for alarm floods are either badly designed alarm management systems (AMS) or causal dependent disturbances which either way, raise an alarm based on a single causal disturbance. These dependencies are difficult to recognize during the engineering of an AMS. This article presents an overview of an algorithm for the automatic alarm data analyzer (AADA). It is able to find possible and significant reasons for alarm floods by identifying the most frequent alarms and those causal alarms consolidating alarm-sequences. They are to be used to improve and to redesign an AMS, so that the alarm flood problem can be reduced at the end.

AB - In the domain of process control, operators face the problem that more alarms are generated than can be physically addressed by a single operator. Such a situation is called alarm flood. The reasons for alarm floods are either badly designed alarm management systems (AMS) or causal dependent disturbances which either way, raise an alarm based on a single causal disturbance. These dependencies are difficult to recognize during the engineering of an AMS. This article presents an overview of an algorithm for the automatic alarm data analyzer (AADA). It is able to find possible and significant reasons for alarm floods by identifying the most frequent alarms and those causal alarms consolidating alarm-sequences. They are to be used to improve and to redesign an AMS, so that the alarm flood problem can be reduced at the end.

KW - Alarm Floods

KW - Alarm Management

KW - Manufacturing

KW - Process Control

KW - Re-Engineering

UR - https://www.scopus.com/pages/publications/84861606029

U2 - 10.1109/SSD.2012.6198008

DO - 10.1109/SSD.2012.6198008

M3 - Conference contribution

AN - SCOPUS:84861606029

SN - 9781467315906

T3 - International Multi-Conference on Systems, Signals and Devices, SSD 2012 - Summary Proceedings

BT - International Multi-Conference on Systems, Signals and Devices, SSD 2012 - Summary Proceedings

T2 - 9th International Multi-Conference on Systems, Signals and Devices, SSD 2012

Y2 - 20 March 2012 through 23 March 2012

ER -

Computing dependent industrial alarms for alarm flood reduction

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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Cite this