A methodology for enhancing the reliability of expert system applications in probabilistic risk assessment

In highly complex industries, capturing and employing expert systems is significantly important to an organization's success considering the advantages of knowledge-based systems. The two most important issues within the expert system applications in risk and reliability analysis are the acquisition of domain experts' professional knowledge and the reasoning and representation of the knowledge that might be expressed. The first issue can be correctly handled by employing a heterogeneous group of experts during the expert knowledge acquisition processes. The members of an expert panel regularly represent different experiences and knowledge. Subsequently, this diversity produces various sorts of information which may be known or unknown, accurate or inaccurate, and complete or incomplete based on its cross-functional and multidisciplinary nature. The second issue, as a promising tool for knowledge reasoning, still suffers from lack of deficiencies such as weight and certainty factor, and are insufficient to accurately represent complex rule-based expert systems. The outputs in current expert system applications in probabilistic risk assessment could not accurately represent the increasingly complex knowledge-based systems. The reason is the lack of certainty and self-assurance of experts when they are expressing their opinions. In this paper, a novel methodology is presented based on the concept of Z-numbers to overcome this issue. A case study in a high-tech process industry is provided in detail to demonstrate the application and feasibility of the proposed methodology.     

Formalisation of normative knowledge for safe design

This paper presents a formal methodology for modelling knowledge included in safety standards. The use of the NIAM/ORM method addresses the problem of unprecise semantics and the misinterpretation introduced by the use of natural languages. It also allows for producing a formal model of the knowledge. This formalisation is a necessary step in order to exploit the knowledge efficiently, but is not sufficient in itself. So, we propose to restructure the normative knowledge, basing this restructuring on a generic structure of engineering views. This multi-criterion approach allows the designer to use standards much easier in this form than in their current textual expression. Furthermore, the resulting formal model of a standard can be implemented. This implementation results in the production of a Computer Aided Safety Standards Application for design (CASSA) tool. This tool allows to analyse various application scenarios, all included in the safety knowledge model, through specific user-oriented interfaces depending on each user's objective. Nevertheless, the implemented model of the safety knowledge is independent and unique with regard to these scenarios. In so doing, our contribution can concern users other than machine designers, such as valuers, standardisation experts or teachers, as well as relate to other areas dealing with standards such as the environment, toy industry, etc.     

“Incivility,social undermining,bullying…oh my!”: A call to reconcile constructs within workplace aggression research

Research in the field of workplace aggression has rapidly developed in the last two decades, and with this growth has come an abundance of overlapping constructs that fall under the broad rubric of workplace aggression. While researchers have conceptually distinguished these constructs, it is unclear whether this proliferation of constructs is adding appreciably to our knowledge, or whether it is constraining the questions we ask. In this paper, I consider five example constructs (i.e., abusive supervision, bullying, incivility, social undermining, and interpersonal conflict) and argue that the manner in which we have differentiated these (and other) aggression constructs does not add appreciably to our knowledge of workplace aggression. I then provide supplementary meta‐analytic evidence to show that there is not a predictable pattern of outcomes from these constructs, and propose a restructuring of the manner in which we conceptualize workplace aggression. Copyright © 2010 John Wiley & Sons, Ltd.     

基于模糊逻辑理论的应急决策冲突程度表示方法研究

针对突发灾害事故应急决策过程中的冲突问题，提出1种应急决策冲突程度的表示方法，将应急决策冲突定量表示出来。基于模糊逻辑理论对应急决策冲突进行模糊评价；通过构建“大多数”的模糊函数，确定冲突程度的表示路径；根据冲突与一致性的相对关系，对“一致性程度”的模糊函数进行改造，构建“冲突程度”的模糊函数，并通过冲突程度的计算过程，得到最终的冲突程度；结合应急决策冲突实际，划分冲突等级，并确定其取值范围。研究结果表明:基于模糊逻辑理论的应急决策冲突程度表示方法充分利用了应急决策专家的决策偏好信息，实现了应急决策冲突程度的定量表示。     

基于知识推理的发电企业设备风险管理应用研究

基于发电企业设备自身的特点及工作人员对风险知识认知的局限性,有必要分析发电企业设备在运行、检修中潜在的风险.分析了设备风险知识与风险管理的关系,并以发电企业各类大型设备中应用最广泛的电动机为例,解决了电动机风险知识的表达及推理问题,为实现基于知识的设备风险管理提供了一种思路,对指导发电企业的设备日常维护、巡检以及状态监测、避免不必要的损失有着积极的意义.     

基于包络线的云相似度及其在安全评价中的应用

在安全评价中,专家给出的数据一般带有定性和定量、模糊性和随机性、不确定性等特点。为了表示这些特点,并将这些信息进行分析、合并,进而达到化简的目的,提出一种基于包络线的云模型方法。该方法用云模型表示专家对某一问题给定的数据,形成多位专家对该问题的多个云模型。同时根据云模型形态特点,构建云模型的上下包络线,并对包络线之间的云滴区域进行积分。最终通过积分区域重叠部分与积分区域的比例关系来判断云模型的相似程度,达到将这些专家信息化简的目的。给出了4种基于相似度的评价语义化简规则。应用该方法分析巷道冒顶风险中稳定岩层距巷道顶板表面距离的中度风险语义。结果表明,两位专家对于该问题的看法既有联系又有区别。最后给出了该算法的优点。     

基于BP神经网络在森林防火专家系统不确定推理中的应用研究

提出将改进的BP神经网络应用于森林防火专家系统的不确定性推理中,其良好的自学习和泛化能力,可以解决基于可信度规则的知识表示在实际应用中导致的规则激增,推理速度缓慢的问题。该方法将不确定的知识用可信度区间表示,通过知识编码,设计并训练BP网络,最后用MATLAB进行仿真。实验结果表明:BP神经网络可以自动学习专家的典型经验,并且能将之准确的推广,隐含层神经元个数的确定和典型样本的选取决定了准确精度。在实际的专家系统不确定推理应用中具有应用价值。     

Epistemic uncertainty in fault tree analysis approached by the evidence theory

Process plants may be subjected to dangerous events. Different methodologies are nowadays employed to identify failure events, that can lead to severe accidents, and to assess the relative probability of occurrence. As for rare events reliability data are generally poor, leading to a partial or incomplete knowledge of the process, the classical probabilistic approach can not be successfully used. Such an uncertainty, called epistemic uncertainty, can be treated by means of different methodologies, alternative to the probabilistic one. In this work, the Evidence Theory or Dempster–Shafer theory (DST) is proposed to deal with this kind of uncertainty. In particular, the classical Fault Tree Analysis (FTA) is considered when input data are supplied by experts in an interval form. The practical problem of information acquisition from experts is discussed and two realistic scenarios are proposed. A methodology to propagate such an uncertainty through the fault tree up to the Top Event (TE) and to determine the belief measures is supplied. The analysis is illustrated by means of two simple series/parallel systems. An application to a real industrial safety system is finally performed and discussed.     

基于模糊神经网络的火灾事故处理专家系统研究

以系统科学和行为科学理论为基础,结合人工神经网络、模糊推理与计算机技术,形成基于模糊神经网络的火灾事故处理专家系统,在火灾发生时为事故处理指挥人员提供良好的决策支持.本文首先给出了基于模糊神经网络的火灾事故处理专家系统的总体框架（任务管理模块,知识库与数据库管理和维护,火灾事故模型管理系统,解释机构,推理机控制系统,信号采集与处理以及结果输出模块）,并说明了各模块的功能;然后着重介绍了该专家系统中知识表示与获取方法,即将计算智能与符号智能结合起来解决专家系统知识获取的“瓶颈”问题;最后介绍该专家系统中知识库建立的方法以及所采用的推理机制,即模糊推理与规则推理相结合的推理方法.     

The digital representation of safety systems at “Seveso” plants and its potential for improving risk management

At Seveso plants, duty holders must have a complex system for assessing and managing risks. The pillars of this system are the safety report and the safety management system, with a number of underlying documents. The strength of the system is the high standardization of these documents. Regulations, standard codes and guidelines define content, structure and formats. The weakness is the high complexity. Managers and workers perceive documents as difficult to understand and far from actual operations. Major threats for the credibility of documents (and therefore for the safety systems) come from the continuous organizational and technical changes, which in a short time can make most documents obsolete; as well as by near misses, which continuously show the holes in safety systems. A big effort is required to follow up the plant changes and the near misses. In order to help safety managers, a new software has been developed. At Seveso plants, it has been possible build an integrated digital representation, because all documents are perfectly structured. This representation may be used both for updating the relevant documents after a change and to improve documents after a near miss or an accident. In this way, safety documents are always up to date and trustworthy and the huge knowledge, which is usually hidden inside safety documents, is clearly revealed and revived. The approach is basically “knowledge based” and the intention is to provide safety managers with an easy and simple tool. IRISonLine is a software that has been developed by ISPESL to provide safety managers of “Seveso” establishments with a tool for improving the management of change and of near misses.     

论安全科学的基础规律与知识体系

安全科学的发展面临基础规律缺乏、知识体系混乱的难题。笔者研讨了"综合属性"论对安全科学发展的阻滞作用,认为普遍存在于各类事物中的安全现象及其规律是安全科学的专属领域;提出安全问题涉及到受损事物、致损事物和二者耦合关系3个要素;论述了受损事物要素的损害可能性和损害防护性问题及其4个理论命题;致损事物要素的损害能力相关性和损害能力可变性问题及其2个命题。分析了耦合关系要素的3种类型及其特点和主要存在领域。在"三要素"安全规律的基础上,给出了安全科学知识体系的3个知识类型和13个知识门类,为构造安全科学的核心知识集提供了整体性思路。     

森林火灾防治决策专家系统的研究与实现

笔者比较系统地收集、研究了林火专家多年积累的理论、经验和解决问题的方法以及各种预测模型、模型的适应条件和使用规则等 ,利用人工智能和COM组件技术 ,通过模型技术和专家系统技术的有机结合 ,建立了基于网络的森林火灾防治决策专家系统。实现了森林火灾从火灾预测、林火扑救决策、清理火场、看守火场到最后的损失评估全过程的推理辅助决策 ;实现了整个决策过程中预测模型和预测结果随外界条件的突变而进行的实时修正 ,从而真正实现了森林火灾管理各个阶段的实时性、准确性和正确性。     

山区村镇洪灾承灾能力评估——以神农架林区为例

针对我国山区村镇洪灾特点,以神农架林区为对象,提出了基于云模型的洪灾承灾能力评价方法。针对山区村镇条件和山洪特点,构建评估指标体系;建立基于逆向云发生器和综合云算法结合专家打分区间和最可能值确定指标权重、使用条件云发生器获得量化指标的评价水平、耦合得到评价结果的评价方法,并对全区八个乡镇的山洪承灾能力进行了评估,为林区规划提供科学依据。结果表明,林区各村镇山洪承灾能力总体较低,孕灾环境恶劣,专项应灾能力明显落后,其中松柏镇、阳日镇、红坪镇和下谷坪乡属于低水平,木鱼镇与新华镇属于较低水平,宋洛乡属于中等水平,九湖镇为高水平。案例结果表明该方法能够直观地将客观数据和主观认识反映为综合结果,有利于获得可靠的结论。     

A Bayesian approach to construct bow tie diagrams for risk evaluation

Bow tie diagrams have become a popular method for risk analysis and safety management. This tool describes the whole scenario of a given risk graphically, and proposes preventive and protective barriers to reduce, respectively, its occurrence and its severity. The weakness of bow tie diagrams is that they are restricted to a graphical representation of different scenarios exclusively designed by experts that ignore the dynamic aspect of real systems. Thus, constructing bow tie diagrams in an automatic and dynamic way remains a real challenge. This paper proposes a new Bayesian approach to construct bow tie diagrams from real data and improve them by adding a new numerical that enables us to implement the appropriate preventive and protective barriers in a dynamic manner.     

应急准备知识库系统设计与实现——以演练方案为例

为解决应急准备过程中普遍存在的“知识断档”问题,提出设计与实现应急准备知识库系统的针对性解决方案,并以演练方案编制为例,从应用实践的角度出发,提出具体思路。定义“知识范畴-知识主体-知识点”3级层次架构,提出包含“输入提取、存储、维护更新、知识应用”在内的应急准备知识库系统定位,归纳由“用户、知识内容、使用场景、应用模式”所构成的应急准备知识库“四要素设计法”。其中,针对知识加工输出这一复杂需求,引入以方案模板设计和智能向导制作为核心的设计实现理念。研究结果为应急准备实操人员逐渐摆脱“知识断档”的困境,以及进一步强化应急准备整体能力,提供了一种可行的思路和方法。     

Handling and updating uncertain information in bow-tie analysis

Bow-tie analysis is a fairly new concept in risk assessment that can describe the relationships among different risk control parameters, such as causes, hazards and consequences to mitigate the likelihood of occurrence of unwanted events in an industrial system. It also facilitates the performance of quantitative risk analysis for an unwanted event providing a detailed investigation starting from basic causes to final consequences. The credibility of quantitative evaluation of the bow-tie is still a major concern since uncertainty, due to limited or missing data, often restricts the performance of analysis. The utilization of expert knowledge often provides an alternative for such a situation. However, it comes at the cost of possible uncertainties related to incompleteness (partial ignorance), imprecision (subjectivity), and lack of consensus (if multiple expert judgments are used). Further, if the bow-tie analysis is not flexible enough to incorporate new knowledge or evidence, it may undermine the purpose of risk assessment.Fuzzy set and evidence theory are capable of characterizing the uncertainty associated with expert knowledge. To minimize the overall uncertainty, fusing the knowledge of multiple experts and updating prior knowledge with new evidence are equally important in addition to addressing the uncertainties in the knowledge. This paper proposes a methodology to characterize the uncertainties, aggregate knowledge and update prior knowledge or evidence, if new data become available for the bow-tie analysis. A case study comprising a bow-tie for a typical offshore process facility has also been developed to describe the utility of this methodology in an industrial environment.     

Differential implications of team member promotive and prohibitive voice on innovation performance in research and development project teams: A dialectic perspective

How and when does team member voice facilitate team innovation? Integrating research on member voice and a dialectic perspective of innovation, we advance a model in which team member promotive voice enhances team innovation through team knowledge utilization, whereas team member prohibitive voice enhances team innovation through team reflexivity in a nonlinear fashion. We further propose that the differential effects of team member promotive and prohibitive voice will be stronger at different stages (idea generation vs. idea implementation) of the innovation cycle. Survey data from 78 research and development project teams showed a positive indirect effect between team member promotive voice and team innovation through team knowledge utilization, although this relationship was also mediated through team reflexivity. Moreover, the indirect effect of team member promotive voice on team innovation via team knowledge utilization was stronger for teams in the idea generation stage of team innovation. Results also confirmed a nonlinear indirect relationship between team member prohibitive voice and team innovation via team reflexivity such that the positive effects of team member prohibitive voice tapered off at high levels. Contrary to our expectations, the effects of prohibitive voice held regardless of stage. Theoretical and practical implications are discussed.     

地铁火灾监控技术发展的德尔菲预见性分析

通过分析地铁火灾监控系统的结构组成和技术组成的发展情况,总结当前地铁火灾监控系统应用领域的各项技术,并以这些技术作为德尔菲调查问卷的内容,按照德尔菲调查的要求设计调查问卷,联络本领域资深专家进行德尔菲调查,统计专家的反馈信息,将反馈信息定量转化为计算值,计算各技术课题指标评价值,定量分析每个技术领域内技术课题影响地铁火灾监控系统发展的重要程度、各技术领域的专家认同重要程度以及技术课题预计实现时间;最终通过重要程度与专家认同重要程度计算出的综合认同重要程度,总结分析出信息处理领域、探测领域、报警和网络通信领域是制约地铁火灾监控系统发展最主要的因素,提出各技术领域的技术大部分都预计在2010-2020年之间实现,其中实现最快的是探测领域内的技术课题。     

How to consolidate Trevor’s experience and knowledge? Impossibilities,reflections on possibilities,and call to action

Looking back, significant progress in process safety and the knowledge to achieve a safe level has been made. Professor Kletz with his wise and concise maxims has shown us in many respects the way to go, yet more direction is needed for transfer of this knowledge to new generations. After a brief problem analysis, a sketch is given of various developments in the field of process safety, such as our knowledge on hazardous properties, hazard and risk analysis tools, human aspects, trends and developments in industry, and future perspectives. Subsequently, an analysis is made of the knowledge infrastructure required to maintain and to improve a knowledge base. In particular, scenario identification and modeling is mentioned. To that end the ‘lessons learned’ in the past should be better used. This has proven not to be easy. A way to go is indicated that in the longer term may reap success. However, in the present climate, funds for research are scarce and that for safety research are scant. Research is not only to develop new knowledge but is also of crucial importance to maintain quality academic education and the formation of ‘teacher of teachers’. A recent initiative is reported to bring this problem to the attention of policy makers worldwide.     

基于模糊数学的石油化工装置HAZOP风险分析技术研究

对传统的HAZOP分析中偏差原因发生可能性进行量化。对于有统计数据的,根据行业数据、公司经验及企业事故建立HAZOP风险分析统计数据库;对于没有统计数据的HAZOP分析偏差原因发生概率,通过专家主观评判,用模糊数理论将专家自然语言转换为模糊数,采用左右模糊排序法将模糊数转换为模糊失效概率值。研究了偏差后果严重程度的划分标准,并根据偏差原因概率和偏差后果严重程度确定风险等级,利用风险矩阵得出偏差风险的大小。从而把HAZOP分析方法从定性改进为半定量的分析方法。据此对石油化工装置进行了HAZOP风险分析。