PFDavg generalized formulas for SIS subject to partial and full periodic tests based on multi-phase Markov models

Innal, Fares; Lundteigen, Mary Ann; Liu, Yiliu; Barros, Anne

doi:10.1016/j.ress.2016.01.022

Cited by 27 publications

(10 citation statements)

References 14 publications

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“…This small movement of the valve has negligible effect on process flow and pressure, so partial stroke testing can be performed without any additional production disturbances that may cause process shutdowns. 8,15 In offshore oil and gas exploration, it is of high importance to reduce the number of planned and unplanned stops. Reducing the number of planned and unplanned stops is important in offshore oil and gas exploration.…”

Section: Dynamic Bayesian Network Modelingmentioning

confidence: 99%

“…In addition, Pascual et al 18 explored the optimal PST interval by considering periodic and non-periodic tests. Innal et al 15 considered the effects of PST and different repair times and established a new generalized formula for SISs by using the multi-phase Markov model. Wu et al 5 modeled the degradation process of the final components with Weibull distribution, proposed a method for reliability assessment of the end-component of SIS with time-varying failure rates, and studied the improvement of the system reliability by PST and FT.…”

Section: Introductionmentioning

confidence: 99%

“…11 In addition, the need to shut down the entire system during functional testing may cause other operational problems. 9,12,13 Since PST can be carried out without interfering with production, PST is introduced as a supplement to FT. 14,15 For HIPPS valves, PST is the partial stroke operation of the valve, which can meet the movement requirements of the valve and detect several dangerous faults.…”

Section: Introductionmentioning

confidence: 99%

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Reliability and availability modeling of Subsea Autonomous High Integrity Pressure Protection System with partial stroke test by Dynamic Bayesian

Wang

Liu

Hou

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part O:

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Subsea Autonomous High Integrity Pressure Protection System is used in the subsea production process to lower the pressure level of downstream equipment and pipelines and to protect low-pressure pipelines and equipment. Once failure occurs, it will cause serious environmental damage and huge economic losses. In this article, a method of Dynamic Bayesian networks is proposed based on different failure types detected by different test methods. The reliability and availability of HIPPS with different detection methods were analyzed quantitatively. The results show that the performance of the system is improved significantly after inspection and maintenance. Compared with traditional methods, the performance of HIPPS is improved after the partial stroke test is introduced. Through sensitivity analysis, it is found that failure rates have a greater impact on the reliability of HIPPS valves. Increasing partial stroke test coverage can improve HIPPS performance. To improve the reliability of HIPPS, it is necessary to improve the reliability of the execution unit, especially the HIPPS valves. The analysis of the PST strategy can provide a theoretical basis for selecting the frequency of partial stroke test and functional test interval in actual projects.

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Section: Dynamic Bayesian Network Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Reliability and availability modeling of Subsea Autonomous High Integrity Pressure Protection System with partial stroke test by Dynamic Bayesian

Wang

Liu

Hou

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part O:

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“…The behavior of systems tested periodically, which is the case of SIS, followed over a time interval of several proof test periods cannot be properly rendered by a classical Markov chain (CMC). Actually, it requires the use of a multi-phase Markov chain (MPMC) (Innal, 2008; Langeron et al , 2008; Mecheri et al , 2015; Innal et al , 2016) where the state’s probabilities at the beginning of each proof test period P ( b i +1 ) are updated from those obtained at the end of the previous period P ( e i ). This update requires the use of a chaining matrix M such that:…”

Section: Oo3 Configuration Modeling Using Markov Chainsmentioning

confidence: 99%

Verification of the IEC 61508 PFH formula for 2oo3 configuration using Markov chains and Petri nets

Omeiri

Hamaidi

Innal

et al. 2020

IJQRM

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PurposeThe purpose of this paper is to check the consistency of the IEC 61508 standard formula related to the average failure frequency (PFH: the probability of dangerous failure per hour) for a commonly used safety instrumented system (SIS) architecture in the process industry: 2-out-of-3 voting (2oo3), also known as Triple Modular Redundancy (TMR).Design/methodology/approachIEC 61508 standard provided PFH formulas for different SIS architectures, without explanations, assuming that the SIS puts the equipment under control into a safe state on the detection of dangerous failure. This assumption renders the use of classical reliability approaches such as fault trees and reliability block diagrams impractical for PFH calculation. That said, the consistency verification was performed thanks to a dynamic and flexible reliability approach, namely Markov chains following these steps: (1) developing the multi-phase Markov chains (MPMC) model for 2oo3 configuration, (2) deducing the related classical Markov chains (CMC) model and (3) deriving a new PFH formula for the 2oo3 architecture based on the CMC model and thoroughly comparing it to that given in the IEC 61508. Moreover, 2oo3 architecture has been modeled through Petri nets for numerical comparison purposes. That comparison has been carried out between the numerical results obtained from IEC 61508 formula, the newly derived formula, Markov chains and Petri nets models.FindingsThe newly obtained formula for 2oo3 configuration contains extra terms compared with the IEC 61508 one. Therefore, this latter formula induces an underestimated PFH results, which is dangerous from a safety point of view. This fact was corroborated by the numerical comparison.Research limitations/implicationsThis paper does not consider the different configurations given in IEC 61508.Originality/valueIn our knowledge, no verification works have been conducted before on the IEC 61508 PFH formulas with shutdown capability. Therefore, the nonaccuracy of the PFH formula related to the 2oo3 has not been stated before. This paper proposes a new and more accurate formula.

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“…Some efforts have been made in the development of PFDavg by integrating with the influence of FT and PT. The generalized PFDavg formulas have been established using the multi-phase Markov models in consideration of partial tests and repair times [32]. Jin and Rausand [15] have developed approximate generalized expressions that can calculate the PFDavg for general k-out-of-n systems subject to partial-testing and common-cause failures.…”

mentioning

confidence: 99%

Reliability modeling of subsea SISs partial testing subject to delayed restoration

Zhang

Zheng

et al. 2019

Reliability Engineering & System Safety

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Subsea oil and gas production has always involved the challenging task of determining the overall reliability of safeguarding systems, such as safety instrumented systems (SISs). Partial testing and delayed restoration of SISs are the main issues in operation and maintenance activities. This paper proposes a novel reliability-modeling methodology for subsea SISs subject to partial testing and delayed restoration. The proposed methodology incorporates an increasing failure rate in conjunction with dangerous undetected failures for the final elements. Approximation formulas for evaluating the average probability of failure on demand are derived for SISs in the lowdemand operating mode. In addition, the effects of degradation are modeled by following Weibull rules in different subsequent partial testing intervals. In contrast to previous works, the present research accounts for delayed restoration after detecting failures and also considers the repair time for different scenarios. The proposed formulas are compared with the existing ones for partial verification. A case study on the shutdown valves of a subsea highintegrity pressure protection system is presented to illustrate the feasibility of the proposed methodology. It is also proven that the proposed approximation offers a robust opportunity for testing strategy optimization and performance improvement of SISs.

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PFDavg generalized formulas for SIS subject to partial and full periodic tests based on multi-phase Markov models

Cited by 27 publications

References 14 publications

Reliability and availability modeling of Subsea Autonomous High Integrity Pressure Protection System with partial stroke test by Dynamic Bayesian

Reliability and availability modeling of Subsea Autonomous High Integrity Pressure Protection System with partial stroke test by Dynamic Bayesian

Verification of the IEC 61508 PFH formula for 2oo3 configuration using Markov chains and Petri nets

Reliability modeling of subsea SISs partial testing subject to delayed restoration

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