Using a system theory based method (STAMP) for hazard analysis in process industry

Different hazard analysis techniques are used in the chemical process industry. Most of these techniques were developed long time ago. There is an argument that significant changes have occurred in the process industry but these techniques have not been modified accordingly. Therefore, there may be limitations in identifying hazards related to the modern process industry in complex sociotechnical environment using these techniques. Recently new hazard analysis techniques based on systems theory have been introduced. STPA (System-Theoretic Process Analysis) is one of these systemic techniques. It has been used in some fields with promising results but with limited application in the process industry. This paper applies STPA to a process plant as an industrial case study. Recommendations generated by STPA are compared with the HAZOP study of the process plant which is a traditional technique. Conclusions are presented on the application of systemic techniques to the process industry as a complementary study to analyze the safety of the system as a whole and also to capture interactions between component of the system. Further studies are required to study STPA in more details and evaluate if it can be used as an alternative to HAZOP.     

On the need for system-theoretic hazard analysis in the process industries

Most process hazard analysis (PHA) studies today are conducted using traditional methods such as the hazard and operability study (HAZOP). Traditional methods are based on a chain-of-events model of accident causality. Current models of accident causality are based on systems theory and provide a more complete representation of the causal factors involved in accidents. Consequently, it is logical to expect that PHA methods should reflect these models, that is, system-theoretic hazard analysis (STHA) should be used. Indeed, system-theoretic process analysis (STPA) has been developed as such a method. STPA has been used in a variety of industries but, at this time, it has not gained acceptance by the process industries. This article explores the reasons for this situation. Expectations for PHA in the process industries are examined and issues for the application of STPA in the process industries are discussed. It is concluded that a variety of matters must be addressed before STPA can be considered as a viable PHA method for the process industries and the case for the use of STHA in the process industries is not yet proven.     

ExSys-LOPA for the chemical process industry

The chemical process industries are characterized by the use, processing, and storage of large amounts of dangerous chemical substances and/or energy. Among different missions of chemical plants there are two very important ones, which: 1. provide a safe work environment, 2. fully protect the environment. These important missions can be achieved only by design of adequate safeguards for identified process hazards. Layer of Protection Analysis (LOPA) can successfully answer this question. This technique is a simplified process of quantitative risk assessment, using the order of magnitude categories for initiating cause frequency, consequence severity, and the likelihood of failure of independent protection layers to analyze and assess the risk of particular accident scenarios. LOPA requires application of qualitative hazard evaluation methods to identify accident scenarios, including initiating causes and appropriate safeguards. This can be well fulfilled, e.g., by HAZOP Studies or What-If Analysis. However, those techniques require extensive experience, efforts by teams of experts as well as significant time commitments, especially for complex chemical process units. In order to simplify that process, this paper presents another strategy that is a combination of an expert system for accident scenario identification with subsequent application of LOPA. The concept is called ExSys-LOPA, which employs, prepared in advance, values from engineering databases for identification of loss events specific to the selected target process and subsequently a accident scenario barrier model developed as an input for LOPA. Such consistent rules for the identification of accident scenarios to be analyzed can facilitate and expedite the analysis and thereby incorporate many more scenarios and analyze those for adequacy of the safeguards. An associated computer program is under development. The proposed technique supports and extends the Layer of Protection Analysis application, especially for safety assurance assessment of risk-based determination for the process industries. A case study concerning HF alkylation plant illustrates the proposed method.     

Model-based hazard identification in multiphase chemical reactors

Chemical productions operated in extreme conditions (high pressure, high temperature) require a detailed analysis of all potentially dangerous situations that can lead to a major industrial accident and thus cause a loss of life and property. Many accidents in the near or distant history underline the need of a detailed safety analysis in process industries, not only in the phase of plant design but also during the operation of the plant. It would be shown that simulation of a chemical unit using an appropriate mathematical model and the nonlinear analysis theory can be a suitable tool for safety analysis. This approach is based on mathematical modeling of a process unit where both the steady-state analysis, including the analysis of the steady states multiplicity and stability, and the dynamic simulation are used. Principal objective of this paper is to summarize problems regarding the model-based hazard identification in processes. A case study, focused on phenomena of multiple steady states in ammonia synthesis reactor will be presented. The influence of the model complexity and model parameters uncertainly on the quality of safety analysis would be underline.     

某焦化企业苯加工系统危险分析

介绍了某焦化企业苯加工系统危险分析的步骤、过程,所解决的技术问题及分析结果,可作为其它焦化企业相关系统进行危险分析时参考。     

Process safety data management program based on HAZOP analysis and its application to an ethylene oxide/ethylene glycol plant

HAZOP analysis is a process hazard analysis method that has been widely applied both within and outside the chemical processing industries. This paper presents a design method for a process safety data management program for petrochemical plants based on HAZOP analysis and demonstrates the steps of application involved in building a process safety data management system for an ethylene oxide/ethylene glycol production plant. Firstly, the production data files and relevant documents of the plants should be classified and stored in the program database as reference documents and treatment schemes for coping with abnormal situations should be collected and summarized as guidance documents. Secondly, the HAZOP analysis method is employed to identify all the dangerous deviations possibly existing in the production process of the ethylene oxide/ethylene glycol plant. Then, the relationships among the deviations, the reference documents and the guidance documents should be considered and evaluated. Finally, each dangerous deviation will be given a corresponding reference document and guidance document. The reference documents and guidance documents stored in the expert system can be utilized to help operators solve the corresponding technical problems and cope with abnormal situations. The process safety data management program will contribute to the identification, analysis and resolution of operation problems. When an abnormal situation occurs, according to the deviations exhibited in the system, the necessary reference documents and guidance documents will be quickly consulted by the operators, and an appropriate decision will be made to address the abnormal situation. Therefore, by using the process safety data management program, plant security and human safety in the petrochemical industries will be improved.     

Model-based HAZOP study of a real MTBE plant

Integration of a mathematical model approach with hazard and operability (HAZOP) analysis is presented in this contribution. The presented analysis is based on the mathematical modelling of a process unit, where both the steady-state analysis (including continuation and bifurcation analyses), and the dynamic simulation are used. The main benefit of this integration is the ability to perform a detail safety analysis for a relatively complicated process. Such an approach may dramatically decrease the possibility that several sources of hazard will be overlooked. Of course, the presented methodology may also seriously reduce the time necessary for the hazard identification process. In this paper, a methyl tertiary-butyl ether (MTBE) production unit was chosen to identify potential hazard and operational problems of a real process. This simplified case-study unit consists of two investigated types of equipment: a tubular fixed bed reactor and a reactive distillation column.     

Safety assessment of the film boiling chemical vapor infiltration (FB-CVI) process through a system-theoretic accident model and process (STAMP)

Film boiling chemical vapor infiltration (FB-CVI) is considered as one of the fastest process methodologies for manufacturing carbon-carbon (C–C) composite products and possesses various advantages compared to conventional methodologies. However, there are safety concerns associated with this process for large-scale manufacturing, mainly owing to the intrinsic nature of the precursor and the process conditions. Considering the multifunctional interactions of the various systems during the process, a system-theoretic process analysis (STPA)/system theoretic accident model and process (STAMP) model is used to perform a safety analysis of the hazardous states of the FB-CVI process at the system level. As a case study, the FB-CVI process equipment employed for the manufacturing of C–C composites is considered. The safety constraints present in the system are assessed for adequacy through a hazard analysis by STPA/STAMP. The analysis through STPA/STAMP demonstrated the capability to create proactive strategies for the design and realization of process equipment that can be employed to manufacture C–C composite products through the FB-CVI process.     

Performance evaluation of process industries resilience: Risk-based with a network approach

Risk management can be defined as coordinated activities to conduct and control an organization with consideration of risk. Recently, risk management strategies have been developed to change the approach to hazards and risks. Resilience as a safety management theory considers the technical and social aspects of systems simultaneously. Resilience in process industries, as a socio-technical system, has four aspects of early detection, error-tolerant design, flexibility, and recoverability. Meanwhile, process industries' resilience has three phases: avoidance, survival, and recovery, determining the transition between normal state, process upset event, and catastrophic event. There may be various technical and social failures such as regulatory and human or organizational items that can lead to upset or catastrophic events. In the avoidance phase, the upset event is predicted, and thus, the system remains in a normal state. For the survival phase, the system state is assumed to be an upset process event, and the system tries to survive through the unhealthy process conditions or remains in the same state, probably with low performance. In the recovery phase, the system is supposed to be catastrophic, and the emergency barriers are prioritized to show the severity of the consequences and response time, leading to a resumption of a normal state. Therefore, a resilience-based network can be designed for process industries to show its inherent dynamic transition in nature. In this study, network data envelopment analysis (DEA), as a mathematical model, is used to evaluate the relative efficiency of the process industries regarding a network transition approach based on the system's internal structure. First, a resilience-based network is designed to consist of three states of normal, upset, and catastrophic events. Then, the efficiency of each industrial department, which is defined as decision-making units (DMUs), is evaluated using network DEA. As a case study, a refinery that is considered a critical process industry is assessed. Using the proposed model shows the efficient and inefficient DMUs in each of three states of normal, upset, and catastrophic events of the process and the projection onto efficient frontiers. Besides calculating the network efficiency, the performance of each state is extracted to precisely differentiate between DMUs. The results of this study, which is one of the fewest cases in the area of performance evaluation of process industries with a network approach, indicated a robust viewpoint for monitoring and assessment of risks.     

Building an Executive Information System for Maintenance Efficiency in Petrochemical Plants—An Evaluation

This study used the manufacturing process in the petrochemical industries as an example and developed a dedicated maintenance programme and executive information system (EIS) for this industry. The software for EIS was established on a CMMS platform, with logical and extractive analysis used to store the information in a KPI databank. The system developed can provide plant managers and engineers with a complete summary of information and keep them updated regarding the present status of their maintenance efforts. The objective of this study was to establish a management system for maintaining knowledge in the petrochemical industries, such as the management of standard operating procedures (SOPs), historical records and the analysis of data for the facility. To design the software, a review of petrochemical facility was purposed to enhance the maintenance efforts and facilitate the decision-making process. The main functions of the system include asset reliability analysis, failure analysis and maintenance benefit cost analysis. For the petrochemical industry, the impact of safety and environment caused by equipment malfunction is more substantial than that of other industries. If executives can manage essential points effectively and make decisions according to a key performance index, risks to safety and environment, which result from equipment malfunction, can be decreased and safety can be enhanced for petrochemical refineries.     

TOPHAZOP: a knowledge-based software tool for conducting HAZOP in a rapid, efficient yet inexpensive manner

Hazard and operability (HAZOP) studies constitute an essential step in the risk analysis of any chemical process industry and involve systematic identification of every conceivable abnormal process deviation, its causes and abnormal consequences. These authors have recently proposed optHAZOP as an alternative procedure for conducting HAZOP studies in a shorter span of time than taken by conventional HAZOP procedure, with greater accuracy and effectiveness [Khan, F. I. and Abassi, S. A., optHAZOP. An effective and efficient technique for hazard identification and assessment Journal of Loss Prevention in the Process Industries, 1997, 10, 191–204]. optHAZOP consists of several steps, the most crucial one requires use of a knowledge-based software tool which would significantly reduce the requirement of expert man-hours and speed up the work of the study team. TOPHAZOP (Tool for OPTmizing HAZOP) has been developed to fulfil this need.

The TOPHAZOP knowledge-base consists of two main branches: process-specific and general. The TOPHAZOP framework allows these two branches to interact during the analysis to address the process-specific aspects of HAZOP analysis while maintaining the generality of the system. The system is open-ended and modular in structure to make easy implementation and/or expansion of knowledge. The important features of TOPHAZOP and its performance on an industrial case study are described.     

基于过程方法的企业安全评价指标体系构建方法

针对安全评价技术的应用现状,分析现有安全评价体系在构建上的局限性,认为安全评价体系应基于现代安全管理体系的运作方式进行构建;回顾安全管理的发展过程,对代表现代安全管理的两种管理模式的起源及特点进行了分析,认为两种管理模式都应用了质量管理的过程方法;在该基础之上,结合过程方法的特点与企业的实际运作方式,提出基于过程方法的安全管理模型,并运用该模型,对安全评价体系的指标构成进行分析;以危险源识别、管理过程、安全教育与培训和应急准备与响应4个指标为基础,构建了安全评价体系的框架。     

Risk assessment of coupling links in hazardous chemicals maritime transportation system

The hazardous chemicals maritime transportation system (HCMTS) belongs to a typical complex tech-social system, which is comprised of multiple functions with interactions. To quantitatively assess the risks triggered by failure coupling links (CLs) between upstream and downstream functions, a hybrid method integrating the Functional Resonance Analysis Method (FRAM), fuzzy set theory, and risk matrix is proposed in the present study. A total of 10 essential functions and 16 CLs involved in HCMTS were identified by FRAM. The fuzzy set theory was adopted to aggregate the weights of risk consequence and likelihood for CLs. A risk matrix with a continuous scale was utilized to assess and rank the CLs’ risks. The results have been demonstrated by the comparisons, indicated that the risk indexes (RIs) of the CLs between the functions < Consignment of HCs> and <Undertaking the transportation>, <Consignment of HCs> and <Declaration of HCs>, <Loading HCs in port> and <Ship navigation at sea > are higher in the whole chain of HCMTS.     

Subjective theories of organizing and learning from events

The present paper outlines potential shortcomings of analyzing events in high hazard systems. We argue that the efficiency of organizational learning within high hazard systems is at least partially undermined by the subjective theories of organizing held by their members. These subjective theories basically reflect an “engineering” understanding of “how a system and its components perform”, and are assumed to involve (social-) psychological blind spots when applied to the analysis of events. More specifically, we argue that they neglect individual motives and goals that critically drive work performance and social interactions in high hazard systems. First, we focus on the process of identifying the causes of failed organizing within the course of an event analysis. Our analysis reveals a mismatch between the basic functional assumptions of the event analyst on the motives of social actors involved in an event and on the other hand, the perspective held by the social actors themselves. Second, we discuss the process of correcting failed social system performance after events. Thereby we draw on blind spots that emerge from the direct application of technical safety principles (i.e., standardization and redundancy) to the organization of social systems. Finally, we propose some future research strategies for developing event analysis methods which are aimed at improving an organization’s learning potential.     

An integrated off-on line approach for increasing stability and effectiveness of automated controlled systems based on pump dependability—case study: Offshore industry

Automated controlled systems are vulnerable to faults. Faults can be amplified by the closed loop control systems and they can develop into malfunction of the loop. A control loop failure will easily cause production stop or malfunction at a petrochemical plant. A way to achieve a stable and effective automated system is to enhance equipment dependability. This paper presents a standard methodology for the analysis and improvement of pump performance to enhance total operational effectiveness and stability in offshore industry based on dependability. Furthermore, it is shown how a reliability–safety analysis can be conducted through equipment dependability indicators to facilitate the mitigation of hazard frequency in a plant. The main idea is to employ principle component analysis (PCA) and importance analysis (IA) to provide insight on the pumps performance. The pumps of offshore industries are considered according to OREDA classification. The approach identifies the critical pump and their fault through which the major hazards could initiate in the process. At first PCA is used for assessing the performance of the pumps and ranking them. IA is then performed for the worst pump which could have most impact on the overall system effectiveness to classify their components based on the component criticality measures (CCM). The analysis of the classified components can ferret out the leading causes and common-cause events to pave a way toward improving pump performance through design optimization and online fault detection which ultimately enhance overall operational effectiveness.     

Organizational Climate Metrics as Safety,Health and Environment Performance Indicators and an Aid to Relative Risk Ranking within Industry

The chemical, pharmaceutical and other related process industries are characterized by inherently hazardous processes and activities. To ensure that considered risk management decisions are made it is essential that organizations have the ability to rank the risk profiles of their assets and operations. Current industry risk ranking techniques are biased toward the assessment of the risk potential of the asset or operation. Methodologies used to assess these risks tend to be engineering-based and include, for example, hazard identification and event rate estimation techniques. Recent research has associated lagging safety performance indicators with metrics of organizational safety climate. Despite the evidence suggesting their potential usefulness, organizational climate metrics have not yet been exploited as a proactive safety, health and environmental performance indicator or as an aid to relative risk ranking. This paper summarizes research that successfully produced a statistical model of organizational climate and its relationship to site significant injury frequency rates, allowing the relative risk ranking of sites based upon organizational climate metrics. The responses to an industrial organizational survey are examined for a pharmaceutical company's sites in the United Kingdom, Sweden and the United States. Projection to Latent Structures Analysis is performed on the survey responses. The resultant models are shown to be able to accurately model the site significant injury frequency rates. The organizational climate metrics that discriminate between the safety performance levels of different sites are identified.     

Dynamic failure assessment of an ammonia storage unit: A case study

Chemical Process Industries usually contain a diverse inventory of hazardous chemicals and complex systems required to perform process operations such as storage, separation, reaction, compression etc. The complex interactions between the equipment make them vulnerable to catastrophic accidents. Risk and failure assessment provide engineers with an intuitive tool for decision making in the operation of such plants. Abnormal events and near-miss situations occur regularly during the operation of a system. Accident Sequence Precursors (ASP) can be used to demonstrate the real-time operating condition of a plant. Dynamic Failure Assessment (DFA) methodology is based on Bayesian statistical methods incorporates ASP data to revise the generic failure probabilities of the systems during its operational lifetime.In this paper, DFA methodology is applied on an ammonia storage unit in a specialized chemical industry. Ammonia is stored in cold storage tanks as liquefied gas at atmospheric pressure. These tanks are susceptible to failures due to various abnormal conditions arising due process failures.Tank failures due to three such abnormal conditions are considered. Variation of the failure probability of the safety systems is demonstrated. The authors use ASP data collected from plant specific sources and safety expert judgement. The failure probabilities of some safety systems concerned show considerable deviation from the generic values. The method helps to locate the components which have undergone more degradation over the period and hence must be paid attention to. In addition, a Bayesian predictive model has been used to predict the number of abnormal events in the next time interval. The user-friendly and intuitive nature of the tool makes it appropriate for application in safety assessment reports in process industries.     

基于半定量的FRAM道路危险品运输事故分析方法研究*

为弥补事故分析法在道路危险品运输事故致因研究方面的缺失,解决传统事故分析方法分析结果不全面、防控措施不具体且针对性较差的问题,引入半定量功能共振事故模型（FRAM）,通过定量化功能上下游耦合变异性,阐述事故发生机理同时,找到系统关键功能和关键链路,制定防控措施重点监控。结果表明:基于半定量的FRAM道路危险品运输事故分析方法能够更快、更准确地找出事故发生的关键功能和关键链路,制定针对性防控措施,有效提高道路危险品运输系统安全性。研究结果可为道路事故分析提供参考。     

基于系统理论事故模型与过程的危险性分析方法

传统危险性分析方法将事故视为开始事件诱发的一连串事件所造成的不幸后果,适于处理相对简单或由物理组件构成的系统,但无法胜 任较为复杂的社会技术系统,有必要研究和探索推广性更好、更为有效的系统安全分析手段。系统理论事故模型与过程（STAMP）将安全视为系 统组件间交互的一种涌现特性,并认为事故起因除了组件失效,组件间交互失常而违背安全约束也是重要诱因。主张在系统开发、设计和运行 中通过加强控制和强化有关安全约束来预防事故。基于此,先引入了STAMP的基本概念,并介绍了其分析步骤,然后,以贴近真实的导弹拦截系 统危险性分析案例,阐述了基于STAMP的分析过程。该分析方法可为开发较高安全性水平的社会技术系统提供技术支持。