安全管理基础知识

海因里希因果连锁理论 海因里希将事故因果连锁过程概括为以下5个因素：遗传及社会环境，人的缺点，人的不安全行为或物的不安全状态，事故，伤害。海因里希用多米诺骨牌来形象地描述这种事故的因果连锁关系。在多米诺骨牌系列中，一枚骨牌被碰倒了，则将发生连锁反应，其余几枚骨牌相继被碰倒。如果移去中间的一枚骨牌，则连锁被破坏，事故过程被中止。他认为，企业安全工作的中心就是防止人的不安全行为，消除机械的或物质的不安全关态，中断事故连锁的进程，从而避免事故的发生。     

近代事故链

正近代事故链之一:1972年,威格斯沃斯(WiggleSworth)对事故链发生的原因进行的总结,提出了教育模型如下:近代事故链之二:博德现代事故因果连锁理论博德(FrankBird)提出了现代事故因果连锁理论,理论认为:事故的直接原因是人的不安全行为、物的不安全状态     

应用事故致因理论解剖事故一起电击工亡的原因分析

参考理论轨迹交叉论该理论认为,在一个系统里,人的不安全行为和物的不安全状态在形成过程中,一旦发生时空运动轨迹交叉,就完会成事故。该理论揭示,事故的发生由三方面因素造成:人的不安全行为,物的不安全状态,管理因素,即空间和时间的调度。环境条件和物的状况不良以及管理上的缺陷,可能形成生产中的事故隐患,由于人为原因的触发,就可能形成事故。因此,事故的发生不外乎是物的不安全状态(或称故障)和人的不安全行为(失误)两大因素共同作用的结果。在能量失控的情况下,人、物两大系统各自运动轨迹的交叉点就构成事故的“时空”。人的不安全行为或物的不安全状态是引起工业伤害的直接原因。     

古典、现代事故致因链在我国煤矿事故分析中的比较研究

事故致因理论是事故的发生机理和理论模型,事故致因链是其核心,是导致事故发生的基本路线。通过对古典事故致因链的代表:海因里希因果连锁理论及现代事故致因链的代表:行为安全"2-4"模型的原因定义、组织概念的引入、链条逻辑关系、事故预防策略等多方面的比较,并应用于一起真实煤矿事故案例分析,发现行为安全"2-4"模型不仅继承和发展了因果连锁理论的优点,更是改进其缺点,在对我国煤矿事故案例分析中更加有效,且在各层级均可找到事故预防的策略。     

安全生产中的事故轨迹交叉论

事故轨迹交叉论足强调人的不安全行为和物的不安全状态相互作用的事故致因理论。该理论强调人的因素和物的因素在事故致因中占有同样重要的地位。可以通过避免人与物两种因素的运动轨迹交义,即避免人的不安全行为和物的不安全状态同时、同地出玑,来预防事故的发生。     

三举措规范违章处理 遏制事故发生

大量研究表明,人是影响安全生产的重要因素,人为因素也是导致许多事故发生的直接原因。分析事故致因理论,轨迹交叉论揭示,通过消除人的不安全行为或物的不安全状态,或避免二者运动轨迹交叉,均可避免事故的发生;能量意外释放理论也指出,能量或危险物质的释放都是由于人的不安全行为或物的不安全状态引起的。人的违章包含在人为因素和人的不安全行为中,故采取管理手段,减少人的违章行为,可直接有效地降低事故发生概率。     

浅谈企业建立职业安全健康管理体系的必要性

海因里希的事故致因理论认为,事故的发生是一连串事件按一定顺序互为因果、依次发生的结果。而人的不安全行为、物的不安全状态是导致事故的直接原因。他认为安全管理就是利用计划、组织、指挥、协调、控制等管理机能,控制来自自然的、机械的、物质的不安全因素和人的不安全行为,即事故发生的致因因素,避免发生事故。     

氧气充装事故预防措施研究

氧气充装事故的发生是人的不安全行为和物的不安全状态相互复杂关联、共同作用的结果。因此,在预防氧气充装事故时必须在弄清事故致因相互关系的基础上采取恰当的措施。     

现代事故因果连锁理论

正亚当斯现代事故因果连锁理论随着人们对事故发生的进一步理解,亚当斯(Edward Adams)提出了一种与博德理论相似的因果连锁模型。该理论把人的不安全行为和物的不安全状态称为现场失误,目的在于提醒人们注意不安全行为和不安全状态的性质。     

某企业的事故预防措施

正众所周知,引起事故的直接原因是人的不安全行为和物的不安全状态,因此事故预防工作必须从这两方面入手。1减少不安全行为针对人的不安全行为所发生的一些隐患,公司采取加强安全教育和落实安全防范措施的对策。凡新员工一进入公司,第一     

基于事故致因理论的供电企业事故分类研究

收集供电企业1961-2008年生产安全事故333起,应用海因里希骨牌理论对事故直接原因进行分类,在此基础上选用北川彻三致因理论对事故的间接原因进行再分类,并进一步通过信息沉淀方法对事故的基本原因进行分类.分类结果表明,企业安全管理缺乏系统性是导致事故的根本原因,为供电行业的安全管理提供了参考.     

浅析事故经济损失

近来,我国各类事故频繁发生,事故造成人员的伤亡或设备、装置、建筑物的破坏,给国家、企业和个人造成了很大的经济损失,也给社会造成了不安定因素.笔者认为事故发生后不仅要查清人员的伤亡情况、事故经过、原因分析、责任人处理、人员教育、措施制定,而且还要弄清事故经济损失的划分,进而对事故经济损失进行分析和统计,从而追究经济损失的承担者.本文介绍了国内外事故经济损失的划分、对比以及计算方法.参照国外的经验,根据我国的实际情况,对于直接损失和间接损失给出了详细的划分和计算的方法.     

Conducting in-depth accident studies

In 1983 the Accident Research Unit at the Institute for Consumer Ergonomics began a major study, sponsored by the UK Department of Transport and three motor companies, to investigate the causes of injury to occupants in car accidents. This study has been under way for nearly ten years and the database of information is one of the most comprehensive of its kind in the world. This information plays a key role in establishing the priorities for safety research in the UK, based on real life accident data. This paper is concerned with the practical aspects of the collection and analysis of real life accident data. Issues include the establishment and maintenance of collaboration with police forces, hospital consultants and coroners; recruitment and training of staff; accident sampling; data quality control and large scale project management. The case is also made for the need to establish a coordinated European database of accident information to facilitate the development of appropriate safety requirements and to set priorities for safety research in Europe.     

Development of a new chemical process-industry accident database to assist in past accident analysis

Past accident analysis (PAA) is one of the most potent and oft-used exercises for gaining insights into the reasons why accidents occur in chemical process industry (CPI) and the damage they cause. PAA provides invaluable ‘wisdom of hindsight’ with which strategies to prevent accidents or cushion the impact of inevitable accidents can be developed.A number of databases maintain record of past accidents in CPI. The most comprehensive of the existing databases include Major Hazard Incident Data Service (MHIDAS), Major Accident Reporting System (MARS), and Failure and Accidents Technical Information Systems (FACTS). But each of these databases have some limitations. For example MHIDAS can be accessed only after paying a substantial fee. Moreover, as detailed in the paper, it is not infallible and has some inaccuracies. Other databases, besides having similar problems, are seldom confined to accidents in chemical process industries but also cover accidents from other domains such as nuclear power plants, construction industry, and natural disasters. This makes them difficult to use for PAA relating to CPI. Operational injuries not related to loss of containment, are also often included. Moreover, the detailing of events doesn’t follow a consistent pattern or classification; a good deal of relevant information is either missing or is misclassified.The present work is an attempt to develop a comprehensive open-source database to assist PAA. To this end, information on about 8000 accidents, available in different open-source clearing houses has been brought into a new database named by us PUPAD (Pondicherry University Process-industry Accident Database). Multiple and overlapping accident records have been carefully eliminated and a search engine has been developed for retrieval of the records on the basis of appropriate classification. PUPAD doesn’t aim to replace or substitute the well established databases such as MHIDAS and MARS but, rather, aims to compliment them.     

FDA事故致因模型在海上船舶碰撞事故安全管理中的运用研究

FDA事故致因模型从安全信息视角出发,将海上船舶碰撞事故发生的宏观与微观因素系统地结合在一起,以管理科学和技术科学为依据,构建海上船舶碰撞FDA事故致因模型,从微观到宏观即个体船只、海运企业、海事局3个层面进行安全信息视域下的事故致因分析,通过逻辑推导定位最佳的安全管理方位。研究结果表明:FDA事故致因模型由3条事故子链及1条事故主链构成,能够从微观到宏观完整表达海上船舶碰撞事故发生过程及机理;破坏3条FDA事故子链或FDA事故主链的形成即可有效地预防海上船舶碰撞事故的发生,对促进海上船舶航行安全管理水平的提高具有重要的理论与现实意义。     

Transferability of accident prediction models

Accident prediction models, the vast majority of which are negative binomial regression models, are of considerable importance to highway agencies since they can be used to conduct many traffic safety studies. However, not every agency possesses sufficient accident statistics that enable it to develop reliable models of its own. This problem gives rise to interest in the transferability of accident prediction models in time and space. It would save time, effort, and money if accident prediction models developed for one region in one period of time could be applied in different time periods and regions to produce reliable safety studies.This paper presents methods for recalibrating negative binomial accident models before transferring them for use in different time periods and regions of space. The paper emphasizes that the recalibration of the shape parameter of a transferred model using local data is absolutely necessary. It explains that it is also desirable to recalibrate the constant term of the transferred model in order to allow the model to better suit local conditions. A moment method is presented for recalibrating the shape parameter of a transferred model when its constant term is not recalibrated. However, a maximum likelihood method is presented for recalibrating both the shape parameter and the constant term of the transferred model and is shown to be superior to the recalibration methods existing in the traffic safety literature.     

What-You-Look-For-Is-What-You-Find – The consequences of underlying accident models in eight accident investigation manuals

Accident investigation manuals are influential documents on various levels in a safety management system, and it is therefore important to appraise them in the light of what we currently know – or assume – about the nature of accidents. Investigation manuals necessarily embody or represent an accident model, i.e., a set of assumptions about how accidents happen and what the important factors are. In this paper we examine three aspects of accident investigation as described in a number of investigation manuals. Firstly, we focus on accident models and in particular the assumptions about how different factors interact to cause – or prevent – accidents, i.e., the accident “mechanisms”. Secondly, we focus on the scope in the sense of the factors (or factor domains) that are considered in the models – for instance (hu)man, technology, and organization (MTO). Thirdly, we focus on the system of investigation or the activities that together constitute an accident investigation project/process. We found that the manuals all used complex linear models. The factors considered were in general (hu)man, technology, organization, and information. The causes found during an investigation reflect the assumptions of the accident model, following the ‘What-You-Look-For-Is-What-You-Find’ or WYLFIWYF principle. The identified causes typically became specific problems to be fixed during an implementation of solutions. This follows what can be called ‘What-You-Find-Is-What-You-Fix’ or WYFIWYF principle.     

故障树分析法在高炉炉前灼伤事故中的应用

应用故障树分析法能系统地分析高炉炉前灼伤的原因，在故障村图上，因果关系明确，并能找出事故发生的主要原因，从而制定措施，以有效地预防事故的发生。