Safety Integrity Level Determination Research Articles

Development and evaluation of a 2oo3 safety controller in FPGA using fault tree analysis and Markov models

The Safety integrity level (SIL) is a measure of the reliability and availability of a safety instrumented system. SIL determination involves qualitative and quantitative analysis based on international standards such as IEC 61508 and IEC 61511. Several techniques can be used to analyze safety instrumented systems, including reliability block diagrams, fault tree analysis, and Markov models. The aim of this paper is to design and evaluate a pressure control system for a compressed nitrogen tank using a PID controller implemented in a field programmable gate array with 2 out of 3 architecture. This architecture ensures the safety of measurements and command of the system through a voting arrangement. The availability of the system is determined by the redundancy and the one hardware failure tolerance. The quantitative analysis is performed by calculating the probability of failure on demand per hour using Markov models or a relevant probabilistic approach based on fault tree analysis. The Markov model method gives the probability of failure of the system in different states during the system life cycle. The fault tree analysis method determines the probability of failure of the system using its equivalent failure rate. Furthermore, this paper compares the SIL result obtained by each model.

A mathematical optimization model for determining safety integrity levels in process facilities

In process industries, Safety Instrumented Functions (SIFs) are implemented to meet government-mandated risk tolerance criteria, which aim to ensure the safety of both individuals and society. The level of risk reduction achieved by a SIF is quantified by its Safety Integrity Level (SIL). Determining the target SILs is a challenging task for facility owners as they must balance the costs and benefits of risk reduction while complying with regulatory requirements. Furthermore, governments define risk tolerance criteria for an overall facility rather than for single scenarios. Therefore, determining a set of SILs for all SIFs becomes imperative to collectively reduce both individual and societal risks to tolerable levels intended for the overall facility. In this paper, we propose a mathematical optimization model to determine the most beneficial collection of SILs that guarantees meeting the risk tolerance criteria. Our model considers both individual and societal risk perspectives and effectively models an overall facility. The proposed model is applied to a process facility and the results are compared with the results from the existing methods for SIL determination. The results demonstrate the model's superior effectiveness in helping owners to select the most beneficial target SILs while ensuring compliance with government requirements.

A Consistent Analytical Method to Assess Reliability of Redundant Safety Instrumented Systems

The significance of determining Safety Integrity Level (SIL) has grown substantially in numerous industry sectors since the publication of international standard for functional safety (IEC61508). To detect SIL using IEC61508, the demand mode must first be recognised. However, there is not any 100% accurate method to identify the demand mode. Design engineers must assume the demand mode based on their assessment of the likely number of failures each year in the system under consideration, referred to as demand rate. This signifies that a defective demand mode assumption leads to an incorrect SIL determination. In addition, the formulas provided by the IEC standards for the SIL determination did not include the demand duration. The majority of prior publications in the literature relied on SIL determination using IEC61508. As a result, the literature suffers from the constraints of the IEC61508 standard, which include ignoring demand duration and uncertainty in assuming the system’s demand mode for determining SIL. This paper addresses the aforementioned issues in literature through proposing a scenario based-formula to calculate Hazardous Event Frequency (HEF) using Markov process for safety system with dual redundancy. The HEF calculated can then be utilized to select SIL while considering the demand duration and obviating the requirement to use the SIS demand mode. The results demonstrated that the proposed method provides higher accuracy in calculating the HEF value compared to the existing traditional formulas.

Safety assessment through HAZOP‐LOPA‐SIL analysis implementation in the DPA demulsifier production process

AbstractIn this paper, the HAZOP‐LOPA‐SIL method is implemented on a safety assessment for an O‐benzenedicarboxylic acid diallyl ester (DPA) demulsifier production process. The risk matrix and tolerable risk criterion are determined with hazard and operability (HAZOP) analysis, and the whole processing technique is divided into nine nodes and seven safety instrumented functions (SIFS). By using guide words and subsequence parameters, the deviation of each node is analyzed, and recommendations are then proposed. After determining the safety integrity level (SIL) of each SIF according to the layer of protection analysis (LOPA) method, the result shows that the SIL of the whole system is SIL1. Considering the influence of mechanical element degradation (valves) on SIL determination, gamma distribution has been adopted to analyze the gradation process. In the serviceable cycle, the minimum PFD average is larger than 0.21 in order to exceed the range of SIL 1. This means that the SIL of the SIF can effectively prevent the failure caused by valve degradation. According to software analysis, the SIL validation result of the whole safety instrument system(SIS) is SIL1.

Parameter uncertainty modeling of safety instrumented systems

In this study, a novel safety integrity level (SIL) determination methodology of safety instrumented systems (SISs) with parameter uncertainty is proposed by combining multistage dynamic Bayesian networks (DBNs) and Monte Carlo simulation. A multistage DBN model for SIL determination with multiple redundant cells is established. The models of function inspection test interval and function inspection test stages are alternately connected to form the multistage DBNs. The redundant cells can have different M out of N voting system architectures. An automatic modeling of conditional probability between nodes is developed. The SIL determination of SISs with parameter uncertainty is constructed by using the multistage DBNs and Monte Carlo simulation. A high-pressure SIS in the export of oil wellplatform is adopted to demonstrate the application of the proposed approach. The SIL and availability of the SIS and its subsystems are obtained. The influence of single subsystem on the SIL and availability of the SIS is studied. The influence of single redundant element on the SIL and availability of the subsystem is analyzed. A user-friendly SIL determination software with parameter uncertainty is developed on MATLAB graphical user interface.

Risk Assessment and Vulnerability Analysis of Liquefied Natural Gas (LNG) Regasification Terminal

Global demand for liquefied natural gas (LNG) is projected to double by 2040, with gas playing a significant role in a less carbon-intensive power system, to 700 million tons. The risk assessment and vulnerability analysis of liquefied natural gas regasification plant have predominant importance due to increase in demand. Determination of safety integrity level (SIL) for process industries becomes a contemporary relevant factor. The reliability of various equipment used in process plants is critically important to maintain safety standards; malfunctions of these instruments may result in accidents which will affect property, environment and people. The main aim of the work is the risk assessment of liquefied natural gas to identify and rank failures that could result in the release of liquefied natural gas to the surrounding environment. In this paper, we integrate fuzzy risk matrix and layer of protection analysis (LOPA) to find safety integrity level value of each Independent Protection Layer (IPL) of seven scenarios of the liquefied natural gas storage facility. Seven scenarios were identified using hazard and operability analysis (HAZOP) as a process hazard analysis (PHA) tool, and we compare the safety integrity level value with Field Device Tool (FDT) method and risk graph is used to find the risk reduction factor (RRF). The safety integrity level determination using fuzzy methods gives more accurate result when compared with the risk graph methods and also describes the safety issues and hazard characteristics in liquefied natural gas terminal and consequence analysis if a liquefied natural gas tanker at the terminal releases liquefied natural gas due to natural and external man-made events, like recent issues between Saudi and Iran regarding oil transporting through Arabian Gulf, and accidents due to projectile effects. Process Hazard Analysis Software Tool (PHAST) and ALOHA software enable to analyse consequence having exorbitant complexity all while considering weather conditions, usage of land and population in the locality. In this paper, atmospheric dispersion modelling and evaluation of flammable and toxic effects have been done by Process Hazard Analysis Software Tool 8.11. Relationship between SIL, PFDavg and RRF is analysed. The frequency, severity and risk values are also gathered. Fuzzy risk values and SIL for each IPL from fuzzy LOPA are obtained, and furthermore, risk reduction SIL values, FDT method to calculate SIL and release scenario are investigated. Comparing the SIL values from fuzzy LOPA approach and FDT method, the consequence analysis of LNG spills from carrier ship due to natural cause using PHAST 8.11 and LNG leak from carrier ship due to man-made cause using ALOHA is also investigated.

Model-Based Functional Safety Analysis of Manufacturing Processes for Weapon Systems

The present study aims to propose a method of carrying out the functional safety analysis to ensure the safety of the manufacturing process for weapon systems. The purpose of using weapon systems is to harm human life and destroy the property of hostile countries. Naturally, a weapon system involves explosives during its development and operation. As such, manufacturing processes for weapon systems have potential hazards of accidents that can cause fatal damages to humans or property. Some erroneous activities in the manufacturing process can produce dangerous results. For this reason, the safety of manufacturing processes in the defense industry domain is more crucial than other general manufacturing domain. To deal with such a safety issue, in this research, we propose a model-based approach to ensuring the safety of the manufacturing process for the defense industry. The proposal is primarily based on the concept of functional safety and includes the three steps: determination of safety integrity levels; selection of appropriate safety analysis methods; and execution of the analysis methods using SysML models. Using the results obtained in the study, one can identify the risk factors in a complex manufacturing environment in advance to take preventive actions against the potential loss that may arise.

New fuzzy uncertainty assessment approach of target SIL evaluation by risk graph optimization

The requirements on the design of safety instrumented systems based on safety integrity level (SIL) have been developed continuously in the oil and gas industries. IEC 61508 and IEC 61511 explain various methods to determine the target SIL for specified safety functions, such as risk graph, risk matrix and layer of protection analysis. These methods could achieve different target SIL for the same safety function, principally due to uncertainty in the models. Additionally, uncertainties in the input parameters donate uncertainty in the output (target SIL). Based on conventional practice in oil and gas industry, engineer usually use different methods such as risk graph, hazardous event severity matrix and LOPA to evaluate target SILs for the same function and accept the most conservative value as the target SIL. In this paper, the uncertainty assessment in target SIL determination evaluated by the risk graph method using new fuzzy set approach has been done and finally a new framework based on this method is proposed.

Determination of Safety Integrity Level of Ammonia Refrigeration System

Determination of Safety Integrity Level of Ammonia Refrigeration System

Функциональная безопасность как неотъемлемая часть инженерных задач

In this paper have been considered the basic terms of functional safety for industrial processes according to GOST R IEC61511–1–2011 «Functional Safety. Safety Instrument Systems for Industrial Processes»: safe and dangerous failures, safety instrumented system, safety instrument function, safety integrity level. The qualitative analysis method — the study of hazard and operability HAZOP using the control words — has been considered. The algorithm for HAZOP carrying out has been presented. Safety integrity levels for low and high intensity of requests have been considered. An example for safety integrity level determination has been depicted.

An adverse outcome pathway framework to support the assessment of DART liabilities of compounds

Recent developments in technology and the move towards efficient utilisation of resources have inspired researchers and practitioners to come up with cost-effective approaches to Safety Integrity Level (SIL) determination and calculation as the current methods are too cumbersome and time-consuming. The bottom line is meeting the organisation's safety requirements in an economical manner regardless of methodology employed without sacrificing accuracy. This paper proposes the Funnel Risk Graph Method (FRGM) as a funnel technique to assess lower SIL ratings, whilst more complex methods can be applied on higher SILs with caution. A review of various target SIL determination and calculation methods in the life cycle of a Safety Instrumented System (SIS) is also presented and compared as per the criteria of relevant qualifying factors. The key outcome of this review is that the qualitative FRGM can be used as a funnel technique to assess lower SIL ratings whilst more complex methods are applied on higher SILs with caution.

Optimization, a rational approach to SIL determination

Abstract In process industry, SIL determination is a risk assessment process through which target Safety Integrity Levels (SIL) are allocated to Safety Instrumented Functions (SIF). A target SIL represents the significance of the hazard against which the SIF protects the plant. This paper introduces new SIL determination methods by taking an optimization approach. Unlike the conventional methods, which are generally focused on calculating the gap between the existing and tolerable levels of risk, the methods introduced in this paper are aimed at optimizing the marginal cost or the benefit-cost ratio. By incorporating the cost factor into the SIL determination process, these methods deliver the most reasonably practicable solutions that can minimize the risk while taking into account the cost of solution. The new methods are formulated for corporate risk and the risk to community (i.e. ALARP). Both methods are derived for demand and continuous modes of SIF operation. Furthermore, a new Safety Index is introduced to combine the SIL and the average Probability of Failure on Demand (PFD) or Frequency of Failure per Hour (PFH). The application of the mathematical models is demonstrated through a practical example from power industry.

HAZOP Study and Determination of Safety Integrity Level Using Fault Tree Analysis on Fuel Gas Superheat Burner of Ammonia Unit in Petrochemical Plant, East Java

Safety is an essential requirement in the course of production in the industry. Security in the factory needs to be considered, especially against malicious nodes such as burner. In this research analysis to determine opportunities hazard that could happen to superheat burner. The magnitude of the risk of harm must be balanced with the security system (SIS). So the system superheat burner analyzed by the method HAZOP and SIL safety level calculated through the method of FTA. Based on research conducted in this thesis, superheat burner has a high danger risk (high risk) component TT-1005 and PT-1018. The level of security superheat burner classified SIL 1 with PFD 4.38x10-2, so do redesign the SIS to achieve SIL 2. PFD system of 0.0099 is achieved by adding 2 ESDV on line check fuel gas and purges gas and increase the pressure switch on each function pressure switch. (PSHH, PSL, PSLL).Â

Overcoming challenges in using layers of protection analysis (LOPA) to determine safety integrity levels (SILs)

The international standard on safety instrumented systems (SISs), IEC 61511/ISA 84, requires the determination of safety integrity levels (SILs) for safety instrumented functions (SIFs) in SISs. Arguably, this is the most important requirement in the standard. Various methods are used for SIL determination including risk matrices and risk graphs, although layers of protection analysis (LOPA) is used increasingly. In employing these methods, a determination must be made as to whether existing risk levels for a process are tolerable by comparing risk estimates with risk tolerance criteria. If a risk gap is found, the SIL required to close the gap is specified. This determination requires setting risk tolerance criteria and making risk estimates.LOPA is used to calculate the risk of individual hazard scenarios. Consequently, in order to simplify the determination of SILs using LOPA, overall risk tolerance criteria often are allocated to individual hazard scenarios so that risk estimates for scenarios can be compared with the allocated criteria. Sometimes hazardous events are used and the risks of scenarios that involve the same hazardous event are aggregated. Unfortunately, allocation of facility risk tolerance criteria to scenarios or events is fraught with difficulties and use of LOPA with allocated risk tolerance criteria can produce inaccurate results within a facility and inconsistent results across facilities.A procedure is provided in this paper for SIL determination using LOPA in which facility risk tolerance criteria are used meaningfully and justifiably. The procedure entails the calculation of overall facility risk and an examination of contributions to the risks to individuals and groups of people from sources of risk such as different types of hazards, different modes of process operation, and different units and processes. The procedure is illustrated with an example.

SIL determination as a utility-based decision process

Using the concept of ALARP (As Low As Reasonably Practicable) and the Expected Utility Theory (EUT), this paper introduces a risk-based optimisation approach to the SIL (Safety Integrity Level) determination process. In the commonly used SIL determination methods the target SIL is determined by comparing the existing level of risk to a pre-set corporate risk target; the gap defines the level of risk that should be reduced by additional layers of protection, such as safety systems. Such methods do not directly factor in the cost impact of the allocated target SILs, nor do they examine the practicability of all SIL alternatives in reducing the risk to as low as possible. The method presented in this paper is based on assigning utility values to different SIL alternatives, in accordance with the cost and benefits of each alternative, and comparing the expected utility values in order to determine the optimum SIL rating as target. A numerical analysis has been developed and applied to the SIL evaluation for a gas turbine over-speed protection to demonstrate the advantages and challenges of the new method.

Correction factor determination on failure rate equation of MacLaurin series for low and high mode application

Abstract Safety Instrumented Function (SIF) is implemented on the system to prevent hazard in process industry. In general, most of SIF implementation in process industry works in low demand condition. Safety valuation of SIF that works in low demand can be solved by using quantitative method. The quantitative method is a simplified exponential equation form of MacLaurin series, which can be called simplified equation. Simplified equation used in high demand condition will generate a higher Safety Integrity Level (SIL) and it will affect the higher safety cost. Therefore, the value of low or high demand rate limit should be determined to prevent it. The result of this research is a first order equation that can fix the error of SIL, which arises from the usage of simplified equation, without looking the demand rate limit for low and high demand. This equation is applied for SIL determination on SIF with 1oo1 vote. The new equation from this research is λ = 0.9428 λ MC + 1.062E−04 H / P , with 5% average of error, where λ MC is a value of λ from the simplified equation, Hazardous event frequency ( H ) is a probabilistic frequency of hazard event and P is Probability of Failure on Demand (PFD) in Independent Protection Layers (IPLs). The equation generated from this research could correct SIL of SIF in various H and P . Therefore, SIL design problem could be solved and it provides an appropriate SIL.

A multiphase dynamic Bayesian networks methodology for the determination of safety integrity levels

A novel safety integrity levels (SILs) determination methodology based on multiphase dynamic Bayesian networks (MDBNs) for safety instrumented systems is proposed. Proof test interval phase and proof test phase are modeled separately using dynamic Bayesian networks, and integrated together to form the MDBNs. The unified structure models of MDBNs for k-out-of-n architectures are constructed, and the procedures of automatic creation of conditional probability tables are developed. The target failure measures, that is, probability of failure on demand, average probability of failure on demand, probability of failing safely, average probability of failing safely, and SIL of safety instrumented systems operating in a low demand mode, are evaluated using the proposed MDBNs. The effects of time interval of MDBNs, common cause weight, imperfect proof test and repair on model precision are researched. User-friendly SIL determination software is developed by using MATLAB GUI to assist engineers in determining the SIL value.

On the use of LOPA and risk graphs for SIL determination

Safety Integrity Level (SIL), as defined in IEC 61511, is a widely used safety performance measure for safety instrumented functions. The standard IEC 61511 suggests several methods for SIL determination, ranging from fully quantitative methods to fully qualitative methods. The large number of safety functions to evaluate during plant design and the need to integrate multidisciplinary design and operation knowledge to achieve effective risk reduction has made necessary the use of multi-disciplinary-team workshop approaches.Two widely used methods in the Oil & Gas industry for SIL determination are Layer of Protection Analysis (LOPA) and Risk Graphs. Each of these methods has their own advantages and disadvantages. LOPA allows the required risk reduction to be incorporated into the SIL values with higher precision. This enables a more detailed consideration of the available protection layers and leaves an objective traceable record of the decision-making process.In contrast, the simplicity of Risk Graphs makes them convenient for screening a large number of safety functions. This can make Risk Graphs useful as a first screening pass prior to using LOPA. However, Risk Graphs are still widely used as a stand-alone method.This paper seeks to explore the differences between LOPA and Risks graphs and to investigate whether the Risk Graphs method can provide the same level of SIL determination rigor as LOPA. The paper aims to determine if the simplicity of Risk Graphs can make that method more efficient for cases when the number of safety functions to evaluate is considerable.

Uncertainty analysis for target SIL determination in the offshore industry

The requirements on the design of SISs (Safety Instrumented Systems) based on SIL (Safety Integrity Level) have been developed continuously in the offshore industry. IEC 61508 and IEC 61511 illustrate various methodologies to determine the target SIL for specified safety functions, such as risk graph, layer of protection analysis, etc. These methods could arrive at different target SILs for the same safety function, mainly due to uncertainty in the models. In addition, uncertainties in the input parameters contribute to uncertainty in the target SIL. In the offshore industry, engineers usually utilize two or more methods to assess target SILs for the same function and take the most conservative value as the target SIL. In this paper, we investigate on the uncertainty in determining target SILs evaluated by the risk graph method, Minimum SIL Table from OLF 070 and LOPA. A procedure of SIL determination accounting for uncertainties is proposed for the risk graph method, Minimum SIL Table from OLF 070 and LOPA by using a Fuzzy Set approach only and the combination of Monte Carlo simulation and Fuzzy Set approach.

SIL determination: Recognising and handling high demand mode scenarios

The International Standards for Functional Safety (IEC 61508 and IEC 61511) are well recognised and have been adopted globally in many of the industrialised countries during the past 10 years or so. Conformance with these standards involves determination of the requirements for instrumented risk reduction measures, described in terms of a safety integrity level (SIL). During this period within the process sector, layer of protection analysis (LOPA) has become the most widely used approach for SIL determination. Experience has identified that there is a type of hazardous event scenario that occurs within the process sector that is not well recognised by practitioners, and is therefore not adequately handled by the standard LOPA approach. This is when the particular scenario places a high demand rate on the required safety instrumented function. This paper will describe how to recognise a high demand rate scenario. It will discuss what the standards have to say about high demand rates. It will then demonstrate how to assess this type of situation and provide a case study example to illustrate how to determine the necessary integrity level. It will conclude by explaining why it is important to treat high demand rate situations in this way and the resulting benefit of a lower but sufficient required integrity level.