Title :
Similarity Analysis of Industrial Alarm Flood Data
Author :
Ahmed, Khandakar ; Izadi, Iman ; Tongwen Chen ; Joe, D. ; Burton, Ted
Author_Institution :
Xstrata Process Support, Falconbridge, ON, Canada
Abstract :
Flooding of alarms is a very crucial problem in process industries. An alarm flood makes an operator ineffective of taking necessary actions, and often risking an emergency shutdown or a major upset. In this work, the flooding of alarms is discussed based on the standards presented in ISA 18.2. A new analysis method is proposed to investigate similar alarm floods from the historic alarm data and group them on the basis of the patterns of alarm occurrences. A case study on real industrial alarm data is also presented to demonstrate the utility of the proposed analysis.
Keywords :
alarm systems; failure analysis; human factors; manufacturing industries; pattern classification; safety systems; ISA 18.2; alarm occurrences; emergency shutdown risk; historic alarm data; industrial alarm flood data similarity analysis; major upset risk; process industries; Algorithm design and analysis; Clustering algorithms; Couplings; Floods; Heuristic algorithms; Vectors; Alarm systems; failure analysis; pattern classification; safety;
Journal_Title :
Automation Science and Engineering, IEEE Transactions on
DOI :
10.1109/TASE.2012.2230627
