.png){kind=icon}
.png){kind=icon}
Return
A data-driven alarm and event management framework
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jlp.2019.103959.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Industrial systems are monitored and controlled by sensors and actuators. The signals from these instruments are mostly configured as alarms in the control system which alerts the plant operators in case of an abnormal process event. A higher number of alarms appearing on the operator screen signifies poor system performance and results in additional workload on the operators and may lead to abnormal situations. These situations can further escalate to a catastrophic incident if not managed properly. There are several solutions available to address the challenges related to the alarms and their management as a part of alarm management life-cycle process defined in industrial standards and guidelines. With the advent of Open Process Automation (OPA) concept and requirement of Real-time Operational Technology (OT) services there is a need to develop solutions based on open source software platforms. To address this, an alarm management framework is proposed, that integrates the alarm management life-cycle concept provided in ANSI/ISA-18.2 with data mining and analysis methods applied on alarm and event logs generated from a control system. The framework involves four distinct levels - design, rationalize, advance, and intelligent. A methodology to benchmark an alarm system by calculating Key Performance Indicators (KPIs) is formulated, results are obtained and shown visually by designing a tool using an open source software platform (R and Python). With the use of data mining and analysis, the methodology/tool benchmarks the system for the defined metrics for alarm systems as KPIs, identifies the bad actors, provides insights about the alarm system to manage the alarm flooding. We use the results to address the key issues and thereby improve the overall efficiency of the alarm system. A historical real industrial Alarm and Event (A&E) log data-set is used as an example to demonstrate the potential application of the proposed alarm management tool, to arrive at reliable decision, contributing to better alarm management and safer operations.
Keywords:
Alarm management
Data mining and analysis
Abnormal situation management (ASM)
Visualization
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.2
Papers:
4.6K
Citations:
1.1W