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Unavailability assessment of redundant safety instrumented systems subject to process demand

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  • Alizadeh, Siamak
  • Sriramula, Srinivas

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.

Suggested Citation

  • Alizadeh, Siamak & Sriramula, Srinivas, 2018. "Unavailability assessment of redundant safety instrumented systems subject to process demand," Reliability Engineering and System Safety, Elsevier, vol. 171(C), pages 18-33.
    • Handle: RePEc:eee:reensy:v:171:y:2018:i:c:p:18-33
    DOI: 10.1016/j.ress.2017.11.011
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    Citations

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    Cited by:

    1. Alizadeh, Siamak & Sriramula, Srinivas, 2018. "Impact of common cause failure on reliability performance of redundant safety related systems subject to process demand," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 129-150.
    2. Azizpour, Hooshyar & Lundteigen, Mary Ann, 2019. "Analysis of simplification in Markov-based models for performance assessment of Safety Instrumented System," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 252-260.
    3. Wu, Shengnan & Zhang, Laibin & Zheng, Wenpei & Liu, Yiliu & Lundteigen, Mary Ann, 2019. "Reliability modeling of subsea SISs partial testing subject to delayed restoration," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    4. Xie, Lin & Lundteigen, Mary Ann & Liu, Yiliu, 2021. "Performance analysis of safety instrumented systems against cascading failures during prolonged demands," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    5. Qi, Meng & Kan, Yufeng & Li, Xun & Wang, Xiaoying & Zhao, Dongfeng & Moon, Il, 2020. "Spurious activation and operational integrity evaluation of redundant safety instrumented systems," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    6. Xing, Jinduo & Zeng, Zhiguo & Zio, Enrico, 2019. "A framework for dynamic risk assessment with condition monitoring data and inspection data," Reliability Engineering and System Safety, Elsevier, vol. 191(C).

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