Safety instrumented functions and safety integrity levels (SIL)

Stavrianidis, Paris; Bhimavarapu, Kumar

doi:10.1016/s0019-0578(98)00038-x

Cited by 24 publications

(7 citation statements)

References 1 publication

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“…This study is limited to SIL within the scope of the design stage. To comply with the standards, a SIL study at the design stage is divided into SIL classification to determine safety requirements and SIL verification to calculate the reliability of a safety function [32]. SIL classification aims to determine the target SIL for an individual safety function in a system, whereas SIL verification is a way to ensure whether the targeted SIL can be satisfied by calculating the probability of failure on demand (PFD) afterward.…”

Section: The Sil Methodsmentioning

confidence: 99%

Application of Industrial Risk Management Practices to Control Natural Hazards, Facilitating Risk Communication

Lee

2018

IJGI

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Establishing a comprehensive management framework to manage the risk from natural hazards is challenging because of the extensive affected areas, uncertainty in predictions of natural disasters, and the involvement of various stakeholders. Applying risk management practices proven in the industrial sector can assist systematic hazard identification and quantitative risk assessment for natural hazards, thereby promoting interactive risk communication to the public. The objective of this study is to introduce methods of studying risk commonly used in the process industry, and to suggest how such methods can be applied to manage natural disasters. In particular, the application of Hazard and Operability (HAZOP), Safety Integrated Level (SIL), and Quantitative Risk Analysis (QRA) was investigated, as these methods are used to conduct key studies in industry. We present case studies of the application of HAZOP to identify climate-related natural hazards, and of SIL and QRA studies that were performed to provide quantitative risk indices for landslide risk management. The analyses presented in this study can provide a useful framework for improving the risk management of natural hazards through establishing a more systematic context and facilitating risk communication.

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Section: The Sil Methodsmentioning

confidence: 99%

Application of Industrial Risk Management Practices to Control Natural Hazards, Facilitating Risk Communication

Lee

2018

IJGI

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“…Moreover, there are several issues inherent in the use of safety integrity levels, such as: the poor harmonization of definition across the different standards that use SIL concept, the derivation of SIL based on reliability estimates, and system complexity (sophisticated safety E/E/PE systems in different technologies designed to perform complicated and critical safety‐related functions). This leads to the misuse of the SIL or making the SIL estimation difficult, as presented below.…”

Section: Sil Use In the Harmonized Risk Management Processmentioning

confidence: 99%

Toward an Application Guide for Safety Integrity Level Allocation in Railway Systems

et al. 2018

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The work in the article presents the development of an application guide based on feedback and comments stemming from various railway actors on their practices of SIL allocation to railway safety-related functions. The initial generic methodology for SIL allocation has been updated to be applied to railway rolling stock safety-related functions in order to solve the SIL concept application issues. Various actors dealing with railway SIL allocation problems are the intended target of the methodology; its principles will be summarized in this article with a focus on modifications and precisions made in order to establish a practical guide for railway safety authorities. The methodology is based on the flowchart formalism used in CSM (common safety method) European regulation. It starts with the use of quantitative safety requirements, particularly tolerable hazard rates (THR). THR apportioning rules are applied. On the one hand, the rules are related to classical logical combinations of safety-related functions preventing hazard occurrence. On the other hand, to take into account technical conditions (last safety weak link, functional dependencies, technological complexity, etc.), specific rules implicitly used in existing practices are defined for readjusting some THR values. SIL allocation process based on apportioned and validated THR values is finally illustrated through the example of "emergency brake" subsystems. Some specific SIL allocation rules are also defined and illustrated.

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“…With proper design, x 3 should be very small consistent with the specified Safety Integrity 6 Level (SIL) [40,41] . Since the interlock system is independent of the alarm system, the success of SS 3 will not depend on factors such as operator skill or alarm sensor fault.…”

Section: Safety Systems and Event Treesmentioning

confidence: 99%

Chemical Process Simulation for Dynamic Risk Analysis: A Steam–Methane Reformer Case Study

Moskowitz

Seider

Soroush

et al. 2015

Ind. Eng. Chem. Res.

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This paper describes how dynamic simulations of a manufacturing process can be used to construct informed prior distributions for the failure probabilities of alarm and safety interlock systems. Bayesian analysis is used starting with prior distributions and enhancing them with likelihood distributions, constructed from real-time alarm data, to form posterior distributions, which are used to estimate failure probabilities. The use of alarm data to build likelihood distributions has previously been investigated [2,11] . Rareevent historical data are typically sparse and have high-variance likelihood distributions.When high-variance likelihood distributions are combined with typical high-variance prior distributions, the resulting posterior distributions naturally have high variances preventing reliable failure predictions. In contrast with prior distributions obtained by maximizing entropy [19] and those that are based on expert knowledge [2] , this paper introduces a new repeated-simulation method to construct informed prior distributions having smaller variances, which in turn leads to posterior distributions with lower variances and a more reliable prediction of the failure probabilities of alarm and safety interlock systems. The application of the proposed method is demonstrated for offline dynamic risk analysis of a steam-methane reformer (SMR) process.

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Safety instrumented functions and safety integrity levels (SIL)

Cited by 24 publications

References 1 publication

Application of Industrial Risk Management Practices to Control Natural Hazards, Facilitating Risk Communication

Application of Industrial Risk Management Practices to Control Natural Hazards, Facilitating Risk Communication

Toward an Application Guide for Safety Integrity Level Allocation in Railway Systems

Chemical Process Simulation for Dynamic Risk Analysis: A Steam–Methane Reformer Case Study

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