Unavailability assessment of redundant safety instrumented systems subject to process demand

Siamak Alizadeh, Srinivas Sriramula

Research output: Contribution to journalArticle

4 Citations (Scopus)
9 Downloads (Pure)

Abstract

The process industry has always been faced with the challenging task of determining the overall unavailability of safeguarding systems such as the safety instrumented systems (SISs). This paper proposes an unavailability model for a redundant SIS using Markov chains. The proposed model incorporates process demands in conjunction with dangerous detected and undetected failures for the first time and evaluates their impacts on the unavailability quantification of SIS. The unavailability of the safety instrumented system is quantified by considering the probability of failure on demand (PFD) for low demand systems. The safety performance of the system is also assessed using hazardous event frequency (HEF) to measure the frequency of system entering a hazardous state that will lead to an accident. The accuracy of the proposed Markov model is verified for a case study of a chemical reactor protection system. It is demonstrated that the proposed approach provides a sufficiently robust result for all demand rates, demand durations, dangerous detected and undetected failure rates and associated repair rates for safety instrumented systems utilised in low demand mode of operation. The effectiveness of the proposed model offers a robust opportunity to conduct unavailability assessment of redundant SISs subject to process demands.
Original languageEnglish
Pages (from-to)18-33
Number of pages16
JournalReliability Engineering & System Safety
Volume171
Early online date22 Nov 2017
DOIs
Publication statusPublished - Mar 2018

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Security systems
Chemical reactors
Markov processes
Accidents
Repair
Industry

Keywords

  • Markov Chain
  • Unavailability Assessment
  • Safety Instrumented Systems
  • Hazardous Event Frequency
  • Process Demand

Cite this

Unavailability assessment of redundant safety instrumented systems subject to process demand. / Alizadeh, Siamak; Sriramula, Srinivas.

In: Reliability Engineering & System Safety, Vol. 171, 03.2018, p. 18-33.

Research output: Contribution to journalArticle

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