Implementing Industry Best Practice Alarm Management

Snelgar, Daniel (2015) Implementing Industry Best Practice Alarm Management. [USQ Project]

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Abstract

This dissertation investigates how alarm management practices can be implemented at a large industrial facility, and what effect this could have on alarm system performance. Poor performing alarm systems create an environment where alarms of high importance can be missed or operators are desensitised to the alarm system. Alarm system performance has been a factor in several high consequence industrial accidents.

The project was conducted at a large coal fired power plant which uses modern Process Control and Human Machine Interface systems. The project site has never employed any alarm management practices in the past and is seeking to implement alarm management practices based on ISA-18.2-2009 Management of Alarm Systems for the Process Industries.

The requirements of industry best practice alarm management were researched and identified. Alarm management processes were created and adopted by the project site. New software tools were developed to support the alarm management processes.

The alarm system performance at the project site was measured using these software tools. The worst performing alarms over a six month period were identified. By investigating the causes of the worst performing alarms improvements were identified that could reduce the alarm rate by 40%.


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Item Type: USQ Project
Item Status: Live Archive
Additional Information: Bachelor of Engineering (Electrical and Electronic) project
Faculty / Department / School: Current - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering
Supervisors: Hills, Catherine
Date Deposited: 01 Jun 2016 00:01
Last Modified: 06 Jun 2016 00:51
Uncontrolled Keywords: alarm management, industrial, industry best, alarm system performance
Fields of Research : 09 Engineering > 0906 Electrical and Electronic Engineering > 090699 Electrical and Electronic Engineering not elsewhere classified
URI: http://eprints.usq.edu.au/id/eprint/29180

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