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Modelling framework for performance analysis of SIS subject to degradation due to proof tests

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  • Srivastav, Himanshu
  • Barros, Anne
  • Lundteigen, Mary Ann

Abstract

Safety Instrumented Systems (SIS) assure safety of equipment/process by performing the safety functions in demand situations. In low-demand mode of operation, final elements of SIS mostly remain idle and safety performance is measured by probability of failure on demand on average (PFDavg). In this mode, SIS are not continuously monitored but subjected to periodic tests (namely proof tests) to ascertain availability for demand situations. Sometimes, proof tests don’t reveal all undetected dangerous failures and may even deteriorate mechanical components by introducing additional stress. To model such degradation phenomena, we propose a framework (based on multiphase Markov process) by adding discrete degraded states between the working and the failed states. The impact of tests is modelled by increasing the transition rates between degraded states. The amplitude increase depends on the current system state at testing time. Then, analytical formulas are developed for the evaluation of the time-dependent PFD under various maintenance policies. Later, a case study on Down hole safety valves (DHSV) is presented to find an optimum test frequency. The optimization problem arises due to the following trade-off: high frequency testing will ensure high availability of DHSV for demand situation, but the stress generated will accelerate degradation to resultant failure.

Suggested Citation

  • Srivastav, Himanshu & Barros, Anne & Lundteigen, Mary Ann, 2020. "Modelling framework for performance analysis of SIS subject to degradation due to proof tests," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    • Handle: RePEc:eee:reensy:v:195:y:2020:i:c:s0951832019301450
    DOI: 10.1016/j.ress.2019.106702
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    References listed on IDEAS

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    1. Wu, Shengnan & Zhang, Laibin & Barros, Anne & Zheng, Wenpei & Liu, Yiliu, 2018. "Performance analysis for subsea blind shear ram preventers subject to testing strategies," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 281-298.
    2. Martorell, P. & Martón, I. & Sánchez, A.I. & Martorell, S., 2017. "Unavailability model for demand-caused failures of safety components addressing degradation by demand-induced stress, maintenance effectiveness and test efficiency," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 18-27.
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    Cited by:

    1. Zhang, Aibo & Hao, Songhua & Li, Peng & Xie, Min & Liu, Yiliu, 2022. "Performance modeling for condition-based activation of the redundant safety system subject to harmful tests," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    2. Misuri, Alessio & Landucci, Gabriele & Cozzani, Valerio, 2021. "Assessment of safety barrier performance in the mitigation of domino scenarios caused by Natech events," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    3. Redutskiy Yury & Balycheva Marina & Dybdahl Hendrik, 2022. "Employee scheduling and maintenance planning for safety systems at the remotely located oil and gas industrial facilities," Engineering Management in Production and Services, Sciendo, vol. 14(4), pages 1-21, December.
    4. Redutskiy, Yury & Camitz-Leidland, Cecilie M. & Vysochyna, Anastasiia & Anderson, Kristanna T. & Balycheva, Marina, 2021. "Safety systems for the oil and gas industrial facilities: Design, maintenance policy choice, and crew scheduling," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    5. Zhang, Aibo & Wu, Shengnan & Fan, Dongming & Xie, Min & Cai, Baoping & Liu, Yiliu, 2022. "Adaptive testing policy for multi-state systems with application to the degrading final elements in safety-instrumented systems," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    6. Zhang, Aibo & Srivastav, Himanshu & Barros, Anne & Liu, Yiliu, 2021. "Study of testing and maintenance strategies for redundant final elements in SIS with imperfect detection of degraded state," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    7. Srivastav, Himanshu & Lundteigen, Mary Ann & Barros, Anne, 2021. "Introduction of degradation modeling in qualification of the novel subsea technology," Reliability Engineering and System Safety, Elsevier, vol. 216(C).

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