Safety Instrumented System Design Research Articles

Cost Effective Analysis of the Design of Safety Instrumented Systems Using Manta-Ray Foraging Optimization Algorithm

Cost Effective Analysis of the Design of Safety Instrumented Systems Using Manta-Ray Foraging Optimization Algorithm

Risk assessment of solid desiccant dehydration package system using safety integrity level‐based safety instrumented system design approach

AbstractThe dehydration package system plays an important role in the stable process operation and production of high‐quality liquefied natural gas by removing water, which is essential for natural gas production. However, as this system operates under various conditions with chemicals, there are threats to safety from potential hazards within the system. Therefore, ensuring system safety can significantly impact the reliable operation of process plants. This study aims to assess the risk of the dehydration package system through the safety integrity level (SIL)‐based safety instrumented system (SIS) design approach as suggested in the International Electrotechnical Commission (IEC) 61,508/61511 standards. Fourteen major hazards requiring recommendations were identified for improving safety through the hazard and operability study (HAZOP). The three major hazards were valve malfunction and gas heater/cooler control failure. Twenty‐one safety instrumented functions (SIFs) in all study nodes were suggested as recommendations to improve safety. Using layers of protection analysis (LOPA), the SIL allocation of the 21 SIFs was performed reasonably with process risks and safeguards. The PDS method was adopted for SIS design and verification, with SIL analysis performed for all the SISs. The results showed that SISs of the dehydration package system satisfied the required SILs.

Safety instrumented system design with credible failure rates: The key to achieving plant safety

AbstractThe influence of the dangerous undetected failure rate, ƛdu, on safety instrumented system (SIS) design has evolved over last 30 years. Now, ƛdu has a significant impact on the SIS design. Using unrealistically low ƛdu can lead to an unsafe SIS design and thus compromise the plant safety. This paper explains some of the reasons why some published ƛdu could be unrealistically low. To address this challenge, ISA TR84 committee Working Group 02 has undertaken an effort to develop a failure rate credibility assessment tool. In this tool, the user will answer a series of questions, and the weighted score of answers will provide a credibility rank for the published device failure rate. This paper will explain the approach of this tool, its target users, and its benefits.

Many-objective robust decision making for efficient designs of safety instrumented systems

A robust decision making framework is proposed to support the appropriate design and use of safety instrumented systems. This framework incorporates many-objective optimization, uncertainty analysis, robustness assessment, scenario discovery and sensitivity analysis to enhance the decision maker’s confidence in selecting a suitable policy and assessing its ability to perform as required under a wide range of plausible states of the word with a clear definition of any existing limitations and vulnerabilities. For this, the probabilistic behavior of safety instrumented systems is taken into account with detailed presentations and discussions of the needed resources and impacts of employing this kind of safety measures. This included capital cost, recurring cost and many aspects of the associated side effects, which covered loss of production, environmental impacts, and ability to intensify existing risks or even trigger new accident scenarios. A detailed application is provided to illustrate the specificity and the outcomes of each involved step.

NSTX-U Personnel Safety System: Safety Instrumented System Development and Design

A safety instrumented system design guided by the International Electrotechnical Commission (IEC) standard IEC/ISA 61511 has been developed to ensure personnel protection from direct radiation and magnetic field hazards identified for the National Spherical Torus eXperiment–Upgrade (NSTX-U) fusion experiment at the Princeton Plasma Physics Laboratory. A layer of protection analysis was performed to develop the performance requirements of the system. A design was developed that incorporated three independent protection layers including configuration-managed safeguards (for electrical hazards), a trapped key system, and a dual chain redundant safety instrumented system. Extensive value engineering was undertaken to supplement existing infrastructure to be compliant with current industry standards and best engineering practices. The development and design of the safety instrumented system is presented.

Safety systems for the oil and gas industrial facilities: Design, maintenance policy choice, and crew scheduling

The technology of oil and gas production is associated with significant hazards. Safety Instrumented Systems (SIS) are designed to ensure proper and safe operations in this sector. This research presents a framework that produces reasonable recommendations (requirements specification) for the SIS design and maintenance with consideration of the three key perspectives relevant to any petroleum engineering project, namely those of facility operators, engineering contractors, and the authorities. The contribution of this research to the area of engineering design is simultaneously addressing the decisions on the SIS design, organization of its maintenance, and employee scheduling for the remotely-located hazardous industrial facilities. These decisions are made based on the choice of maintenance policies incorporated into a Markov model of the system functioning. Another contribution of this research to the reliability modeling area is incorporating diverse redundancy into the modeling and decision-making framework. Thus, this research explores a trade-off between the capital investments into the SIS’s design complexity and the operational expenditures associated with system maintenance and expected losses due to potential hazards. The developed multi-objective decision-making framework requires a black-box optimization approach to produce results. This research is relevant to engineering departments and contractors specializing in designing technological solutions for the petroleum sector.

Genetic Algorithm Optimization Model for Determining the Probability of Failure on Demand of the Safety Instrumented System

A more accurate determination for the Probability of Failure on Demand (PFD) of the Safety Instrumented System (SIS) contributes to more SIS realiability, thereby ensuring more safety and lower cost. IEC 61508 and ISA TR.84.02 provide the PFD detemination formulas. However, these formulas suffer from an uncertaity issue due to the inclusion of uncertainty sources, which, including high redundant systems architectures, cannot be assessed, have perfect proof test assumption, and are neglegted in partial stroke testing (PST) of impact on the system PFD. On the other hand, determining the values of PFD variables to achieve the target risk reduction involves daunting efforts and consumes time. This paper proposes a new approach for system PFD determination and PFD variables optimization that contributes to reduce the uncertainty problem. A higher redundant system can be assessed by generalizing the PFD formula into KooN architecture without neglecting the diagnostic coverage factor (DC) and common cause failures (CCF). In order to simulate the proof test effectiveness, the Proof Test Coverage (PTC) factor has been incorporated into the formula. Additionally, the system PFD value has been improved by incorporating PST for the final control element into the formula. The new developed formula is modelled using the Genetic Algorithm (GA) artificial technique. The GA model saves time and effort to examine system PFD and estimate near optimal values for PFD variables. The proposed model has been applicated on SIS design for crude oil test separator using MATLAB. The comparison between the proposed model and PFD formulas provided by IEC 61508 and ISA TR.84.02 showed that the proposed GA model can assess any system structure and simulate industrial reality. Furthermore, the cost and associated implementation testing activities are reduced.

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.

Optimal plant layout considering the safety instrumented system design for hazardous equipment

The safety of the process plant depends on the adequate separation between the assets and the hazardous units, along with the installation of protection devices. Several mathematical approaches have been proposed to reduce the risk of the explosions through the solution of the facility layout problem, but no model has included the design of the safety instrument systems. In this work, a MINLP approach was developed to solve three issues at the same time: the process equipment layout, the facility layout, and the safety instrumented system design. This approach aims to find the optimal facility layout that minimizes the land cost, the pipeline cost, and the lifecycle cost of each safety instrumented system, reducing the risk of explosions and keeping safety as much as possible the plant assets. The model was applied to find the optimal facility layout of ethylene oxide plant for different tolerable risk frequencies. In this way, this approach provides valuable information during the design stage and substantial support for decision-makers.

Pilot Study on the Application of Employee Scheduling for the Problem of Safety Instrumented System Design and Maintenance Planning for Remotely Located Oil and Gas Facilities

Abstract The technology of production, transportation, and processing of oil and gas involves various hazardous processes. To mitigate the risk that these processes pose, the technological solutions work closely with the automated control and safety systems. The design and organisation of maintenance for the automated safety instrumented systems (SIS) have a significant bearing on the overall safety of operations in this industry. Over the past few decades, many hydrocarbon resources have been discovered in unconventional environments, such as remote, offshore, and arctic locations. Transportation of engineering personnel to these remote locations and back, and thereby, the organisation of the shift work poses additional challenges for the petroleum sector. Under such circumstances, the workforce-related costs play a considerable role in the overall cost of the technological solution and thereby the decisions regarding the workforce organisation should be addressed in the framework of evaluating and choosing the appropriate safety measures. That is why the research presented in this paper aims to address the lifecycle of the technological solution integrating the problems of SIS design, maintenance planning, and employee scheduling into a single decision-making framework to optimise the set of technical and organisational safety measures inherent in the SIS. The performance and maintenance of the SIS are described with a Markov model of device failures, repairs and technological incidents occurrence. The employee scheduling part of the mathematical model utilises the set-covering formulation of maintenance crews taking particular trips. A black-box optimisation algorithm is used to find reasonable solutions to the integrated problem of engineering design and workforce planning. The decisions include the choices of the components and structures for the safety system, the facility overhaul frequencies, the maintenance personnel size, as well as the schedules of trips and shifts for the crews.

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

Abstract 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.

Modelling and Design of Safety Instrumented Systems for Upstream Processes of Petroleum Sector

The adequacy of the decision-making regarding the specification of Safety Instrumented Systems (SIS) deployed for hazardous processes, contributes to avoiding incidents and corresponding losses. This paper proposes an approach to mathematically and economically substantiated design of SIS. Markov analysis is used for the stochastic process of SIS failures and technological incidents occurrence. The model is used further for multi-objective optimization of SIS design. The research is relevant to engineering departments and contractors, who specialise in planning and designing the technological solution.

Optimal Design of Safety Instrumented Systems for Pressure Control of Methanol Separation Columns in the Bisphenol a Manufacturing Process

A bisphenol A production plant possesses considerable potential risks in the top of the methanol separation column, as pressurized acetone, methanol, and water are processed at an elevated temperature, especially in the event of an abnormal pressure increase due to a sudden power outage. This study assesses the potential risks in the methanol separation column through hazard and operability assessments and evaluates the damages in the case of fire and explosion accident scenarios. The study chooses three leakage scenarios: a 5-mm puncture on the methanol separation column, a 50-mm diameter fracture of a discharge pipe and a catastrophic rupture, and, simulated using Phast (Ver. 6.531), the concentration distribution of scattered methanol, thermal radiation distribution of fires, and overpressure distribution of vapor cloud explosions. Implementation of a safety-instrumented system equipped with two-out-of-three voting as a safety measure can detect overpressure at the top of the column and shut down the main control valve and the emergency shutoff valve simultaneously. By applying a safety integrity level of three, the maximal release volume of the safety relief valve can be reduced and, therefore, the design capacity of the flare stack can also be reduced. Such integration will lead to improved safety at a reduced cost.

Method for assigning safety integrity level (SIL) during design of safety instrumented systems (SIS) from database

A SIL assignment method for the design and rectification of SIS used for preventing failure action and spurious activation is presented in this paper. The method has two stages, including SIL assignment based on experience and SIL assignment based on risk quantitative calculation results. SIS experience information, stored in a SIS experience knowledge database, comprises of equipment, SIS names and SIL information, which is summarized from many different SIS design packages of petrochemical units and SIS evaluation reports. In the stage of the SIL assignment based on experience, the SIL of SIS for a unit could be assigned by common SIS information retrieved from the experience knowledge database. In the stage of the SIL assignment based on risk quantitative calculation results, according to IEC 61511, a risk matrix is established to determine tolerable risks. A SIS initial event failure data table and a protective layer failure data table are established and the data could be obtained from certain common databases, such as OREDA, CCPS. The data will be used to calculate and identify residual risks after applying safeguards according to the Layer of Protection Analysis (LOPA) method. The SIL of SIS can be acquired from the calculation results of residual risks and tolerance risks. The combination use of the two stages can generate a method which could be applied in the SIS design of new-built or old-improved units. A SIL assignment program for the design and rectification of SIS is developed to help SIL-assigning. The software include three modules, a module of SIL assignment based on experience, a module of SIL assignment based on risk quantitative calculation results, and a module of SIL verification. Experience data and risk quantitative calculation results will contribute to the design of SISs for equipment systems. A residual oil hydrogenation unit is taken as an example to illustrate the design and rectification method for SIS.

PFDavg generalized formulas for SIS subject to partial and full periodic tests based on multi-phase Markov models

IEC 61508 is a standard on design and operation of safety-instrumented systems (SISs) which has been adapted by many national regulations as the recommended way to achieve high-reliability systems. Many decisions about the design of SIS rely on the results from reliability assessments. It is therefore important that the reliability assessments are able to capture key properties of the system, such as the consideration of regular partial and full proof tests. IEC 61508 has proposed analytical formulas for commonly used architectures. Unfortunately, these formulas do not explicitly include the contribution of partial tests and consequently their use is mainly restricted to full proof tests. In addition, the already existing formulas dealing with partial tests disregard the different repair times. The aim of this paper is to (i) extend the PFDavg formulas given in IEC 61508 by including partial tests impact and, (ii) investigate their consistency based on multi-phase Markov models related to 1oo1 and 1oo2 architectures and (iii) to establish new generalized formulations in light of the results related to the investigation process, which account for the different repair times. Different comparisons are performed throughout the paper in order to validate the set of the derived formulations.

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.

Safety and operational integrity evaluation and design optimization of safety instrumented systems

The control of risks generated by modern industrial facilities could not be guaranteed without the use of safety instrumented systems (SIS). The failure of SIS to achieve their assigned functions could result in huge consequences with respect to both (i) the safety of the monitored system (relating to the SIS safety integrity) as well as (ii) its production availability due to false trips (relating to the SIS operational integrity). Furthermore, these two aspects are usually antagonistic. Therefore, the assurance of this double performance comes first by a thoughtful design of SIS. In that case, the aim of this paper is twofold. First, it focuses on the establishment of generic analytical formulations allowing the assessment of the SIS performance regarding safety integrity and operational integrity. Second, it deals with SIS architecture design optimization. The optimization problem is firstly addressed by a preliminary search for a balance between the above two quantities relying on the analysis of the structure of KooN architectures. Then, a more general and suitable approach based on genetic algorithms is proposed, where several performance indicators and the costs of purchase and maintenance are expected to be considered simultaneously. This general approach is illustrated through an application example.

Critical Systems: a New Approach in Mitigation Control Layer

The inherent complexity of critical production systems, coupled with policies to preserve people's safety and health, environmental management, and the facilities themselves, and stricter laws regarding the occurrence of accidents, are the motivation to the design of Safety Control Systems that leads the mitigation functionality. According to experts, the concept of Safety Instrumented Systems (SIS) is a solution to these types of issues. They strongly recommend layers of risk reduction based on hierarchical control systems in order to manage risks, preventing or mitigating faults, or to lead the process to a safe state. Additionally some of the safety standards such as IEC 61508, IEC 61511, among others, guide different activities related Safety Life Cycle design of SIS. The IEC 61508 suggests layers of critical fault prevention and critical fault mitigation. In the context of mitigation control system, the standard provides a recommendation of activities to mitigate critical faults, by proposing control levels of mitigation. This paper proposes a method to implement the mitigation layer based on the risk analysis of the plant and the consequences of faults of its critical components. The control architecture, based on distributed and hierarchical control systems in a collaborative way, will make use of the techniques of risk analysis raised and mitigation actions, based on the knowledge of an expert, implemented by fuzzy logic. The mitigation layer therefore seeks to reduce the inherent risk in a process, and besides proposing the mitigation layer, this work aims to a further reduction of process risk on proposing an anticipatory mitigation action through temporal analysis of the evolution of the parameter used to measure the effect of the occurrence of a critical fault.

Uncertainty assessment of reliability estimates for safety-instrumented systems

Reliability estimates play a crucial role in decision making related to the design and operation of safety-instrumented systems. A safety-instrumented system is often a complex system whose performance is seldom fully understood. The safety-instrumented system reliability estimation is influenced by several simplifications and assumptions, both about the safety-instrumented system and its operating context, and therefore subject to uncertainty. If the decision makers are not aware of the level of uncertainty, they may misinterpret the results and select a safety-instrumented system design that is either too complex or too simple, or with an inadequate testing strategy, to provide the required risk reduction. This article elucidates the uncertainties related to safety-instrumented system reliability estimation. The article is limited to safety-instrumented systems that are operated in a low-demand mode, for which the probability of failure on demand is the standard reliability measure. The uncertainty of the probability of failure on demand estimate is classified as completeness uncertainty, model uncertainty, and parameter uncertainty and each category is thoroughly discussed. It is argued that the completeness uncertainty is the most important for safety-instrumented system reliability analyses, followed by parameter and model uncertainty. It is further argued that uncertainty assessment should be an integrated part of any safety-instrumented system reliability analysis, and that the analyst should communicate her judgment about the uncertainty to the decision-makers as part of the analysis results.

Safety and Security Integration in LPG Tank Farm Process Control

Safety process control of storage facilities represents the trend for down stream industries, due to high costs that traditional operation implies. Also, maintenance of old facilities is very poor and poses hazards and risks to the safety of operators and surrounding communities. Complete safety and security concepts for the process control can mitigate the need for 24/7 safety operation, increase availability and reliability. Knowledge and experience are key factors involved in the studies and analyses that lead to efficient safety instrumented systems design and implementation.