New PFH-formulas for k-out-of-n:F-systems

Jin, Hui; Lundteigen, Mary Ann; Rausand, Marvin

doi:10.1016/j.ress.2012.11.007

Cited by 23 publications

(12 citation statements)

References 14 publications

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“…Whilst the main benefit of Markov models is accuracy and flexibility according to the specific feature of each mode, establishing a Markov model of k out of n (koon) with a high value of n, can be time consuming and error prone [17][18][19]. Signoret et al [20] employed Petri Nets to categorise safety instrumented systems.…”

Section: Introductionmentioning

confidence: 99%

Unavailability assessment of redundant safety instrumented systems subject to process demand

Alizadeh

Sriramula

2018

Reliability Engineering & System Safety

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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.

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Section: Introductionmentioning

confidence: 99%

Unavailability assessment of redundant safety instrumented systems subject to process demand

Alizadeh

Sriramula

2018

Reliability Engineering & System Safety

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“…In this system degradation based method, CCF part of PFD G is quantified by using the multi-β factor model [22] introduced in PDS method [23] by SINTEF, new information are the quantification method for independent part of PFD G and two sets of general formulae to determine PFD G of any MooN(D) voting group with diverse redundancy, which are the new contributions of this paper. Some other generalized formulae for identical redundancy can be found in [2][3][4]13,24,25].…”

Section: Introductionmentioning

confidence: 99%

SIL verification for SRS with diverse redundancy based on system degradation using reliability block diagram

Ding

Wang

Jiang

et al. 2017

Reliability Engineering & System Safety

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“…The PFD avg /PFH may be calculated on the basis of several reliability assessment methods: simplified formulas, 2–4 IEC 61508 1 formulas, generalized analytical expressions, 3,5 Markov methods and Petri nets. 2 Common for many of the methods is the assumption about constant failure rate.…”

Section: Introductionmentioning

confidence: 99%

Analytical formulas of PFD and PFH calculation for systems with nonconstant failure rates

Rogova

Lodewijks

Lundteigen

2017

Proceedings of the Institution of Mechanical Engineers, Part O:

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Most analytical formulas developed for the PFD and PFH calculation assume a constant failure rate. This assumption does not necessarily hold for system components that are affected by wear. This article presents methods of analytical calculations of PFD and PFH for an M-out-of-N redundancy architecture with nonconstant failure rates and demonstrates its application in a simple case study. The method for PFD calculation is based on the ratio between cumulative distribution functions and includes forecasting of PFD values with a possibility of update of failure rate function. The approach for the PFH calculation is based on simplified formulas and the definition of PFH. In both methods, a Weibull distribution is used for characteristics of the system behavior. The PFD and PFH values are obtained for low, moderate and high degradation effects and compared with the results of exact calculations. Presented analytical formulas are a useful contribution to the reliability assessment of M-out-of-N systems. KeywordsReliability assessment, nonconstant failure rates, Weibull distribution, average probability of failure on demand, average frequency of dangerous failures, analytical formulas Date

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New PFH-formulas for k-out-of-n:F-systems

Cited by 23 publications

References 14 publications

Unavailability assessment of redundant safety instrumented systems subject to process demand

Unavailability assessment of redundant safety instrumented systems subject to process demand

SIL verification for SRS with diverse redundancy based on system degradation using reliability block diagram

Analytical formulas of PFD and PFH calculation for systems with nonconstant failure rates

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