Risk information in decision-making: definitions,requirements and various functions

Inappropriate decisions are often regarded as causes of major accidents in the process industries. To improve the quality of decisions, it is important to make the right information available at the right time. The objective of this work is to investigate what types of risk information is needed for risk-related decisions in various decision-making processes. A framework is proposed to facilitate future research for easing information deficiency. In this paper, risk information is examined through common decision-making processes, and is identified serving to 1) detect and characterize risk-related decision problems, 2) indicate the severity and urgency of decisions, 3) state requirements and constraints of workable solutions, 4) represent attributes for comparing and evaluating solutions, and 5) act as rules to maintain safety or control risk. These usages of risk information in different decision problems imply the large diversity in information needs for decision-making. An adaptive information support is thus suggested to provide targeted risk information to specific decision-makers for effective and efficient decision-making in accident prevention in the process industries.     

基于风险的化工园区布局优化决策支持系统

为加强化工园区风险辨识和布局优化,主要研究化工园区布局优化决策支持系统。在分析该系统主要功能的基础上,介绍基于风险的化工园区布局优化决策支持系统的理论模型:对化工园区重大危险源事故预测建模,包括重大危险源事故发生概率预测和事故后果预测;从个人风险、社会风险和财产风险3个模型评价化工园区区域动态风险,依据这3种风险值,计算区域综合风险;分别就功能区布局、消防布局和交通布局,对化工园区提出动态布局优化方法和建议措施。通过理论模型建立决策系统软件,结合实证分析,证明该决策支持系统的合理性。     

DomPrevPlanning: User-friendly software for planning domino effects prevention

Chains of accidents, in literature generally referred to as domino effects, knock-on effects, cascade effects or escalation effects occur very infrequently but with disastrous consequences. There exist very few software packages to study such domino accidents in complex industrial areas and to forecast potential catastrophes caused by secondary order (involving a sequence of three installations submitted to two consecutive accidents), tertiary order or even higher order accidents. Moreover, available domino software focuses on risk assessment and on consequence assessment. None of these toolkits specifically addresses the prioritization of installation sequences in an industrial area in order to facilitate objective prevention decisions about domino effects. This paper describes the application of a new computer-automated tool designed to support decision-making on preventive and protective measures to alleviate domino effects in a complex surrounding of chemical installations. Using a holistic approach and thus looking at the entire industrial area as a whole, all sequences of three installations in the area are ranked according to their danger contribution to domino effects. An example of a cluster of chemical plants demonstrates the level of qualitative and quantitative input data required. The example is also used to explain the toolkit results, as well as the surplus value and the benefits for company safety managers and regulators.     

Decision analysis on fire safety design based on evaluating building fire risk to life

This study presents a framework of decision analysis on fire safety design alternatives based on evaluating building fire risk to life. A probabilistic risk assessment method for occupant life is presented with consideration of some uncertainties of evacuation process and fire development at first. For occupant evacuation time assessment, occupant pre-movement time is characterized by normal distribution. For onset time to untenable conditions assessment, its uncertainty is considered as probability distribution according to the range of design fires. Based on event tree technique, probable fire scenarios are analyzed with consideration of the effect of fire protection systems, employees extinguishing, etc. It is difficult to make a precise assessment on probability and consequence of every fire scenario, but their lower bound and upper bound can be achieved based on statistical data. Therefore, Supersoft Decision Theory [Malmnäs, P.E., 1995. Methods of Evaluation in Supersoft Decision Theory. Department of Philosophy, Stockholm University, 365 Stockholm; Johansson, H., Malmnäs, P.E., 2000. Application of supersoft decision theory in fire risk assessment. Journal of Fire Protection Engineering 14, 55–84] that allows decision maker to utilize vague statement is utilized to integrate with risk assessment to make decision on different fire safety design alternatives. To express how to make decision on different fire safety design alternatives based on evaluating building fire risk to life, two hypothetical fire safety design alternatives for a commercial building are presented.     

小城镇基础设施防灾减灾决策支持系统的研究与开发

利用信息技术研究灾害问题成为研究热点之一 ,但在小城镇防灾减灾方面仍缺少应有的关注和重视。笔者将地理信息系统 (GIS)和决策支持系统 (DSS)集成应用于开发“基于GIS的小城镇基础设施防灾减灾决策支持系统” ,简要介绍了该系统研制目标和原则、系统结构框架及各子系统的功能 ,解决了系统实现过程中的一系列关键技术 :快速、高效构建小城镇基础空间数据库及三维可视化、应急预案及历史灾情库的电子化及各类灾害分析模拟的专业模型等。实践证明 ,基于基础设施、灾害源、防护保卫目标、应急救援力量的可视化与数字化 ,该系统能够实现对其进行科学管理、对各单一灾种的模拟分析以及应急决策支持 ,有效提高小城镇政府的应急指挥决策水平 ,增强其灾害应急反应能力。     

基于前景理论和BWM的深基坑支护方案综合评价

针对深基坑施工工程的复杂性及决策者风险态度对多指标决策的影响,构建了融合前景理论的深基坑施工支护最优方案选择模型。首先建立深基坑支护方案优选决策问题的多目标评价指标体系,借鉴TOPSIS思想将正、负理想方案作为决策者参照值,在此基础上,进一步将灰色关联分析法引入前景理论定义了正、负价值函数;通过BWM方法得出各指标的客观权重,根据权重函数得到决策者对客观权重的主观评价,在此基础上计算每个备选方案的综合前景值并排序,获得最优支护方案。最终通过两个工程实例验证了模型的有效性,并通过与其他方法比较说明了该模型在准确性方面的优势。     

Recursive Operability Analysis as a decision support tool for Risk-Based Maintenance

This work was developed with the support of MEMC, one of the most important producers of ultra-pure silicon wafers for electronic applications throughout the world. The availability of ultra-pure water is of prime importance in the silicon production process. In order to maximize the availability of UP water, MEMC has developed a preventive maintenance program and a detailed record of each maintenance intervention is recorded. This has allowed a complete failure rate data bank to be developed. In order to optimize the maintenance intervention, a Recursive Operability Analysis (ROA) has been used as a decision support tool. The results of the ROA, coupled with the failure rates, have made it possible to calculate the expected number of events (ENE) of various top events (TEs). The magnitude of each TE has been estimated on the basis of the monetary losses provoked by each event. The risk then has been calculated and the events ranked on this basis. Maintenance policies have been optimized with the aim of reducing the risk of the top ranked events.     

Environmental emergency decision support system based on Artificial Neural Network

We present a general methodology for developing environmental emergency decision support systems (EEDSS) based on an Artificial Neural Network (ANN). We highlight the method for developing the system using an illustrative example of an unexpected atmospheric accident with an ANN prototype system for a district in Shanghai. The network architecture of the ANN is introduced. Then the development process and key technologies are addressed. The procedures for matching the environmental emergency decision support characteristics are as follows: (1) digitization (coding) of case information and emergency measures, in which the information of cases are divided into the input attributes and decision-making information, and standardized and digitized through the Feature Evaluation (FE) method and the Intensity Hierarchical (IH) method, respectively; (2) construction of environmental emergency ANN, in which Gradient Descent with Momentum and Adaptive Learning Rate (GDMALR) method (traingdx function), a modified back-propagation algorithm, is employed to do training; and (3) translation (decoding) of decision-making information, in which output data of ANN is interpreted into practical contingency measures with Translation Based on Conventional Import Ratios (TBCIR) method. The training features, time, errors, accuracy, and input attribute weights of the prototype system are analyzed. The usage of the prototype system is demonstrated through a hypothetical case. This article encounters the challenge of ANN’s own lack of training samples. We discuss to the concept of integrating Case-Based Reasoning (CBR), Genetic Algorithm (GA), and ANN to overcome this difficulty and form a technology system for generating useful decision support information for environmental emergency response.     

Dynamic approach to risk management: Application to the Hoeganaes metal dust accidents

Several major accidents caused by metal dusts were recorded in the past few years. For instance, in 2011, three accidents caused by iron dust killed five workers at the Hoeganaes Corp. facility in Gallatin, Tennessee (USA). In order to prevent such accidents, a dynamic approach to risk management was defined in this study. The method is able to take into account new risk notions and early warnings and to systematically update the related risk. It may be applied not only in the design phase of a system, but also throughout the system lifetime as a support to a more precise and robust decision making process. The synergy of two specific techniques for hazard identification and risk assessment was obtained: the Dynamic Procedure for Atypical Scenarios Identification (DyPASI) and the Dynamic Risk Assessment (DRA) methods. To demonstrate its effectiveness, this approach was applied to the analysis of Gallatin metal dust accidents. The application allowed collecting a number of risk notions related to the plant, equipment and materials used. The analysis of risk notions by means of this dynamic approach could have led to enhanced hazard identification and dynamic real-time risk assessment. However, the approach described is effective only if associated to a proper safety culture, in order to produce an appropriate and robust decision making response to emerging risk issues.     

基于GIS的铁路行车事故救援系统研究

笔者扼要探讨了构建基于GIS的铁路行车事故救援系统的相关理论和方法 ,提出了该系统的设计目标、功能结构、体系结构以及空间数据库设计的简要准则和空间数据的输入方法。笔者还介绍了结合实际科研项目 ,开发的大秦线事故救援辅助决策支持系统。该系统具有以下几方面的特点 :在以工务信息为主体的基础上 ,实现了车、机、工、电、辆各部门主要业务信息以及事故救援预案信息的初步整合 ;实现了线路录像按里程点播以及录像与线路设备综合图的联动 ;实现了事故救援的辅助决策支持 ,提供了一个可以扩展的理想平台。     

Bayesian networks make LOPA more effective,QRA more transparent and flexible,and thus safety more definable!

Quantitative risk analysis is in principle an ideal method to map one’s risks, but it has limitations due to the complexity of models, scarcity of data, remaining uncertainties, and above all because effort, cost, and time requirements are heavy. Also, software is not cheap, the calculations are not quite transparent, and the flexibility to look at various scenarios and at preventive and protective options is limited. So, the method is considered as a last resort for determination of risks. Simpler methods such as LOPA that focus on a particular scenario and assessment of protection for a defined initiating event are more popular. LOPA may however not cover the whole range of credible scenarios, and calamitous surprises may emerge.In the past few decades, Artificial Intelligence university groups, such as the Decision Systems Laboratory of the University of Pittsburgh, have developed Bayesian approaches to support decision making in situations where one has to weigh gains and costs versus risks. This paper will describe details of such an approach and will provide some examples of both discrete random variables, such as the probability values in a LOPA, and continuous distributions, which can better reflect the uncertainty in data.     

基于RBI的碳五石油树脂装置风险评估分析

从技术特点、实施效用等方面,对QRA与RBI两类风险评估技术进行比较,选择使用RBI技术方法对碳五石油树脂装置内静设备及管道实施风险评估。运用挪威船级社的ORBIT Onshore软件定量计算评估范围内设备、管道风险值,评定风险等级,辨识隐患设备,然后从后果、可能性两方面分析产生风险的主要影响因素,经分析得知碳五石油树脂装置受H2S、HCl腐蚀减薄影响轻微,但NaOH导致的碱应力腐蚀对聚合反应后序工段中部分管道设备失效可能性影响较大。最后根据装置内存在的不同损伤机理提出检验优化策略,为装置定期检验工作提供科学的决策支持。     

区域风险评价方法研究

基于定量风险评价的基本原理,提出一种区域风险评价方法。主要针对有多个重大危险源存在的区域,在对单个危险源进行风险评价的基础上,应用叠加原理得到描述该区域整体风险状况的定量评价结果。同时考虑了消防部门和医疗机构在事故应急救援中的积极作用,并将其量化为区域风险的补偿系数。通过实例验证了该方法的可行性,展示了该方法的应用效果。区域风险评价方法不仅能够反映区域风险的分布状况,而且对区域重大危险源的规划和布局具有较好的决策支持作用。     

Participative multi-actor safety screening of infrastructures

Infrastructure planning very often underestimates safety issues in the early design phase. The reason for this is not necessarily the overwhelming importance of other aspects, such as functionality and economic considerations. Rather, the controversial views on safety held by different safety experts accounts for the major reason for not attributing safety the importance it deserves. In this paper we propose a seven-step methodology that allows multiple decision makers to evaluate infrastructure alternatives using safety and other indicators in early project phases. The methodology is based on analytic risk assessments, where the decision makers are asked to make ordinal tradeoffs among different safety, economic, and subjective aspects. The methodology allows multiple decision makers to aggregate preferences for different alternatives evaluated by different decision makers in a participative fashion. The proposed methodology was implemented in the Multimedia Group Decision Support Room at Delft University of Technology. The methodology was validated using real decision makers to show its realism and potential for participative decision making in safety planning.     

Stress and team performance: principles and challenges for intelligent decision aids

Advances in computer technology and artificial intelligence are providing powerful capabilities for developing intelligent decision aids (IDAs) to support operating teams in managing complex systems. Early system designs, which acted as independent computer advisors, constrained human decision making, were brittle and encountered problems of user acceptance. As a result, there has been a shift towards making IDAs more cooperative in assisting users to make decisions under stress. Although there is a growing body of research on how to design IDAs as collaborate team players, this article provides additional insights by focusing on the competencies manifested by efficient teams in adapting to stress. To this extent, a survey of how teams adapt their decision-making strategies, cooperation patterns and team structure has provided a good basis for proposing design principles for collaborative IDAs. The article concludes with some challenges for further developments in information technology and research needs in the area of teamwork under stress.     

GIS在化工园区事故应急救援辅助决策中的应用

采用GIS平台与应急决策支持技术相结合,以园区高危工艺和重大危险源作为分析对象,开发化工园区安全管理系统中的应急救援辅助决策模块,针对园区内高危工艺或重大危险源事故后果预测与事故应急救援管理的科学性和有效性,扩展为对整个化工园区的事故风险管理与事故应急救援辅助决策支持。运用该模块可实现园区内突发事故后果预测、最优救援和疏散路径规划、应急辅助决策方案生成,有效提高化工园区事故救援的科学性和效率,减少人员伤亡和财产损失,提高化工园区安全管理水平。     

事故定性分析与事故定量预测

分析了影响事故预测准确的原因,综述了国内外许多学者在事故预测方面所做的努力。指出今后事故预测工作的主要途径是由安全系统工程专家建立计算机支持的决策支持系统(DSS),由安全专家灵活运用这个系统中的计算机辅助研究方法(CAR)。     

城市重大危险源区域风险评价方法研究

针对城市应急管理的特点,提出了一种城市重大危险源区域风险评价方法。在ARAMIS方法的基础上,对严重度计算进行了修订,引入了急性暴露指南（AEGL）标准对事故后果进行分区;同时,增加了与应急救援效率相关的指标进行风险目标的脆弱性评估;利用GIS技术,对严重度和脆弱性进行叠加分析,绘制出城市重大危险源区域风险地图。以液氨储罐毒气泄漏事故为例,对文中提出的方法进行了验证。实例分析表明,此方法为快速获取城市重大危险源区域风险的空间分布格局提供了新思路,对于降低城市突发环境污染事故的影响和辅助决策者制定科学的城市公共安全管理决策具有一定的现实意义。