Evaluation Of Safety Integrity Level Research Articles

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.

Safety integrity level evaluation of nuclear centrifugal pump based on performance degradation data

To reduce personnel and equipment risks related to centrifugal pumps in nuclear power plants, safety integrity level for centrifugal pumps must be evaluated. The safety integrity level evaluation m...

Hazop Study and Fault Tree Analysis for Calculation Safety Integrity Level on Reactor-C.5-01, Oil Refinery Unit at Balikpapan-Indonesia

plat former reactors are reactors that are in the plat forming unit is designed for developing your specific hydrocarbon molecules that are used in catalytic engine fuel in boiling point range naphtha and fuel mixture to produce components with a higher octane value. Plat former reactor system failure may disrupt operations in the oil processing refinery unit. These circumstances will cause the supply plaformat as products of the plat forming unit valued high octane which is the main raw material of gasoline blending system is reduced. Resulting in decreased production consequency large losses. The failure of the reactor system can also be harmful to the operator, the environment and there is a possibility of reactor unit may explode. To avoid these risks we conducted studies identify hazards that occur in the process rector Hazard and operability (HAZOP) analysis and calculate the value of safety integrity level (SIL). In this study reviewed three nodes Overview consisting of node stage 1, stage 2 and stage 3. Based on the results of identification are thirteen instruments on the third node, which includes equipment; PC-193, FI-005, PC-194 and FI-010. Standards-based Service Oriented systems have Unacceptable risk criteria and the criteria of likelihood 4 Consequences worth three. As for the evaluation of SIL is known that C-5-01 reactor system has two safety Integrity Function (SIS) located in the path of fuel gas and pilot gas lines of the reactor heater. Both SIS has a vote = 1oo3 architecture with similar characteristics, and a review of the SIS has a security level SIL = 2 with a value of PFD = 0.00103.

Identify SIF and specify necessary SIL, and other IPLs, as part of PHA/HAZOP - or - why it is not necessary to “boldly go beyond HAZOP and LOPA”

This article shows how to apply the qualitative definition of IPLs within the setting of a process hazard analysis (PHA) to get most of the gain from Layer of Protection Analysis (LOPA) without doing a LOPA (without using numerical values). The article includes an implementation path to develop PHA leader competencies to guide the qualitative approach. We also show the way we use a PHA team to identify when a SIF is needed and to select the proper target safety integrity level (SIL). This portion of the SIL evaluation and the identification and labeling of the IPLs during the PHA/hazard and operability analysis (HAZOP) does not take any longer than a normal PHA/HAZOP, once the right habits are established. Note that this approach eliminates the need for a separate SIL Evaluation Study to identify the SIFs and select the target SIL. Finally, the article ties together these two specific topics, along with the topic of making risk judgments, to show there is less than 5% need to go beyond HAZOP, and less than 0.01% need to go beyond LOPA. © 2016 American Institute of Chemical Engineers Process Saf Prog 35: 349–359, 2016

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.

Sophisticated Calculation of the 1oo4-architecture for Safety-related Systems Conforming to IEC61508

With the publication and enforcement of the standard IEC 61508 of safety related systems, recent system architectures have been presented and evaluated. Among a number of techniques and measures to the evaluation of safety integrity level (SIL) for safety-related systems, several measures such as reliability block diagrams and Markov models are used to analyze the probability of failure on demand (PFD) and mean time to failure (MTTF) which conform to IEC 61508. The current paper deals with the quantitative analysis of the novel 1oo4-architecture (one out of four) presented in recent work. Therefore sophisticated calculations for the required parameters are introduced. The provided 1oo4-architecture represents an advanced safety architecture based on on-chip redundancy, which is 3-failure safe. This means that at least one of the four channels have to work correctly in order to trigger the safety function.

A Fuzzy Probabilistic Approach for Determining Safety Integrity Level

The process industry has always been faced with the difficult task of determining the required integrity of safeguarding systems such as safety instrumented systems (SISs). The ANSI/ISA S84.01-1996 and IEC 61508 safety standards provide guidelines for the design, installation, operation, maintenance, and test of SIS. However, in the field, there is a considerable lack of understanding of how to apply these standards to both determine and achieve the required safety integrity level (SIL) for SIS. Moreover, in certain situations, the SIL evaluation is further complicated due to the uncertainty on reliability parameters of SIS components. This paper proposes a new approach to evaluate the ldquoconfidencerdquo of the SIL determination when there is an uncertainty about failure rates of SIS components. This approach is based on the use of failure rates and fuzzy probabilities to evaluate the SIS failure probability on demand and the SIL of the SIS. Furthermore, we provide guidance on reducing the SIL uncertainty based on fuzzy probabilistic importance measures.

The Impact of Data Uncertainty in Determining Safety Integrity Level

With the approval of ISA/ANSI S84.01, more and more efforts are necessary to meet desired safety targets. Statistical data are used to calculate the overall system availability or SIL. Failure rates depend on many factors, including the function of the equipment in the system and the definition of failure, the process environment and the maintenance practices, and the type of equipment and its manufacturer. In the process industry, the operating conditions and environments can change dramatically for the same equipment, and the range of failure rates observed can be quite wide. Borrowing data from laboratory and generic data sources introduces an element of uncertainty. Using point values may result in misleading evaluation of safety integrity level (SIL) of a safety instrumented system (SIS). The impact of data uncertainty on the calculation of SIL is discussed in this paper, and procedures to deal with data uncertainty in determining SIL for an SIS is proposed.

Evaluation of safety instrumented systems using reliability analysis

AbstractThe authors have developed a new safety instrumented system (SIS) evaluation method based on reliability analysis. It evaluates the Safety Integrity Level (SIL) using Fault Tree Analysis (FTA). When the SIL falls short of the system's target level, this method can raise it through reliability analysis and system retrofit. A hazard evaluation was carried out on the 415V diesel bus to verify the SIL evaluation method. The availability of the original 415V diesel bus was 99.40%, which comes under the category of SIL 2. After exchanging the diesel generator and the isolator switch using the developed evaluation method, the availability rose to 99.94%, SIL 3.

Performance-based standards: safety instrumented functions and safety integrity levels

This paper discusses two international performance-based standards, ANSI/ISA S84.01 and IEC d61508 and the requirements they place upon companies that rely on electrical, electronic and programmable electronic systems to perform safety functions. Performance-based regulations are also discussed and common safety elements between the standards and regulations are identified. Several risk analysis techniques that can be used to comply with the aforementioned requirements are discussed and a simple example is used to illustrate the use, advantages and disadvantages of the techniques. The evaluation of safety integrity level (SIL) of the Safety Instrumented System (SIS) in terms of the probability to fail to function is outside the scope of this paper.