Determination of the health of a barrier with time-series data: How a safety barrier looks different from a data perspective

Paul Singh, Neil Sunderland, Coen van Gulijk

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Determination of the health of a safety barrier study was performed at the Syngenta Huddersfield Manufacturing Centre, Leeds Road, West Yorkshire, United Kingdom. This work focused on the creation of a BowTie that is augmented with data to monitor the core functions of safety barriers for a loss of control situation on a batch reactor. The performance was determined with industry softwares: Seeq was used to extracted time-series AVEVA Factory Historian was the data warehouse that stored all IoT data from the factory for many years. The data was cleansed and additional tags were required using the analytical software along with the creation of signal conditions and composite conditions to aid in the analysis. This work demonstrates that a barrier looks very different if data is the starting point. Theoretical views of barriers using the detect-decide-act obfuscate a complex data network of IoT parts that all play a role in barrier performance. Another observation is that this particular approach makes it possible to further assess barrier performance and health online.

Original languageEnglish
Article number104889
Number of pages8
JournalJournal of Loss Prevention in the Process Industries
Volume80
Early online date6 Oct 2022
DOIs
Publication statusPublished - 1 Dec 2022

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