Incorporating process demand into models for assessment of safety system performance

Bukowski, Julia V.

doi:10.1109/rams.2006.1677435

Cited by 21 publications

(22 citation statements)

References 1 publication

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“…Most research focuses entirely on those two mechanisms of SIS performance, which leads to the lack of representation of technological incidents in the models. Few works [6,17,18] attempt to incorporate occurrence of incidents into a Markov model. However, in most cases, the authors stick to aggregated models, where the multiple modes of SIS failure or multiple functions of SIS are represented with generalized states of the model.…”

Section: Overview Of the Research Areamentioning

confidence: 99%

“…The approach to modelling is largely based on the ideas presented in [17] and [18], meanwhile the necessary adaptations are made for the purpose of further calculation of costs and other specifics considered in this work. The model of lifecycle cost follows the logic of [10] and its adaptation in [16], with additional modifications for the necessity of this research.…”

Section: Modelling Assumptionsmentioning

confidence: 99%

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Optimization of Safety Instrumented System Design and Maintenance Frequency for Oil and Gas Industry Processes

Redutskiy¹

2017

Management and Production Engineering Review

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Oil and gas industry processes are associated with significant expenditures and risks. Adequacy of the decisions on safety measures made during early stages of planning the facilities and processes contributes to avoiding technological incidents and corresponding losses. Formulating straightforward requirements for safety instrumented systems that are followed further during the detailed engineering design and operations is proposed, and a mathematical model for safety system design is introduced in a generalized form. The model aims to reflect the divergent perspectives of the main parties involved in oil and gas projects, and, therefore, it is formulated as a multi-objective problem. Application of black box optimization is suggested for solving real-life problem instances. A Markov model is applied to account for device failures, technological incidents, continuous restorations and periodic maintenance for a given process and safety system configuration. This research is relevant to engineering departments and contractors, who specialize in planning and designing the technological solution.

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Section: Overview Of the Research Areamentioning

confidence: 99%

Section: Modelling Assumptionsmentioning

confidence: 99%

Optimization of Safety Instrumented System Design and Maintenance Frequency for Oil and Gas Industry Processes

Redutskiy¹

2017

Management and Production Engineering Review

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“…for measuring the effects of system architectures [6,14,20], effects of testing strategies [11,19], different demand modes and associated measures [1,7,9,13], and varying modeling methods [2,5]. More information about research achievements and directions of SISs can be found in [15,16].…”

Section: Introductionmentioning

confidence: 99%

Proof-testing strategies induced by dangerous detected failures of safety-instrumented systems

Liu

Rausand

2016

Reliability Engineering & System Safety

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Some dangerous failures of safety-instrumented systems (SISs) are detected almost immediately by diagnostic self-testing as dangerous detected (DD) failures, whereas other dangerous failures can only be detected by proof-testing, and are therefore called dangerous undetected (DU) failures. Some items may have a DU-and a DD-failure at the same time. After the repair of a DD-failure is completed, the maintenance team has two options: to perform an insert proof test for DU-failure or not. If an insert proof test is performed, it is necessary to decide whether the next scheduled proof test should be postponed or performed at the scheduled time. This paper analyzes the effects of different testing strategies on the safety performance of a single channel of a SIS. The safety performance is analyzed by Petri nets and by approximation formulas and the results obtained by the two approaches are compared. It is shown that insert testing improves the safety performance of the channel, but the feasibility and cost of the strategy may be a hindrance to recommend insert testing.

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“…While being in FD state, it does not cause unsafe failure of a system, but it increases the chances if a demand occurs [7] . System fails unsafe when it is in DD or DU state at the instant of demand.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, the basic model of IEC 2 and Bukowski [1,2,7] is extended to incorporate demand rate, conversion of dangerous failures to safe failures following diagnosis or prooftest and effect of safe failures. A new safety index considering demand rate, probability of failure on actual demand (PFAD) is defined.…”

Section: Introductionmentioning

confidence: 99%

Analyzing effect of demand rate on safety of systems with periodic proof-tests

Kumar

Verma

Srividya

2007

Int J Automat Comput

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Quantitative safety assessment of safety systems plays an important role in decision making at all stages of system lifecycle, i.e., design, deployment and phase out. Most safety assessment methods consider only system parameters, such as configuration, hazard rate, coverage, repair rate, etc. along with periodic proof-tests (or inspection). Not considering demand rate will give a pessimistic safety estimate for an application with low demand rate such as nuclear power plants, chemical plants, etc. In this paper, a basic model of IEC 61508 is used. The basic model is extended to incorporate process demand and behavior of electronic-and/or computer-based system following diagnosis or proof-test. A new safety index, probability of failure on actual demand (PFAD) based on extended model and demand rate is proposed. Periodic proof-test makes the model semi-Markovian, so a piece-wise continuous time Markov chain (CTMC) based method is used to derive mean state probabilities of elementary or aggregated state. Method to determine probability of failure on demand (PFD) (IEC 61508) and PFAD based on these state probabilities are described. In example, safety indices of PFD and PFAD are compared.

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Incorporating process demand into models for assessment of safety system performance

Cited by 21 publications

References 1 publication

Optimization of Safety Instrumented System Design and Maintenance Frequency for Oil and Gas Industry Processes

Optimization of Safety Instrumented System Design and Maintenance Frequency for Oil and Gas Industry Processes

Proof-testing strategies induced by dangerous detected failures of safety-instrumented systems

Analyzing effect of demand rate on safety of systems with periodic proof-tests

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