Occupational Cognitive Failures and Safety Performance in the Workplace

Introduction. The majority of industrial accidents occur because of human errors. Human error has different causes, however, in all cases cognitive abilities and limitations of human play an important role. Occupational cognitive failures are cognitively-based human errors that occur at work. The aim of this study was to examine the relationship between occupational cognitive failures and safety consequences. Method. Personnel of a large industrial company in Iran filled out an occupational cognitive failure questionnaire (OCFQ) and answered questions on accidents. Univariate and multiple logistic regression analysis were used to determine the relationship between cognitive failures and safety consequences. Results. According to developed regression models, personnel with a high rate of cognitive failure, in comparison to low rate, have a high risk of minor injury involvement (OR 5.1, 95% CI [2.62, 10.3]); similar results were for major injury and near miss. Discussion. The results of this study revealed usefulness of the OCFQ as a tool of predicting safety-related consequences and planning preventive actions.     

基于事故统计分析的地铁运营安全管理研究

为了预防和减少地铁运营事故的发生,本文通过统计分析某城市地铁5年的运营事故资料,探讨了地铁运营事故的发生规律,从人、机、环、管几个方面分析了导致地铁运营事故发生的主要原因。结果显示:统计年度内地铁运营事故年度总量较为平稳,事故的发生对月份变化敏感度较低,受气象条件影响较小;信号故障、车辆故障是发生最频繁的事故类型,合计占事故总数的56%。事故原因分析显示,设备设施因素导致的事故占事故总数的87%;人为因素导致的事故占事故总数的7%。根据地铁运营事故特点,从人、机、环、管4方面提出了相应的安全管理对策,可为制定科学合理的地铁运营安全管理措施提供依据。     

企业本质安全化模型研究

随着我国工业的发展,各类事故发生的频率和严重程度都呈现增大的趋势,给国家和个人都带来极大的损失。传统的安全管理模式已不适应现代企业。通过对中国近年来多起大型事故的分析,结合国外工业化进程中事故发生的规律,在对事故致因理论分析的基础上,借鉴本质安全型电器设计思想,根据中国目前工业发展的实际,提出企业本质安全化模型。主要包括5大模块即人的本质安全、机具设备的本质安全、工作环境的本质安全、管理的本质安全和企业安全文化。通过在煤炭企业的应用和实践,大大控制了事故率和人身伤亡。     

煤矿安全生产协同监控系统分析与设计

针对煤矿安全生产多套监控系统并存的现状,通过将煤矿系统模块化,形成了基于安全信息管理数据库的安全生产协同监控系统.该系统能够以工作场所为单位综合分析各类安全信息,协调各部门的安全生产工作,为其提供参考,同时节约资源,减少操作人员,提高危险源辨识准确性,预测事故并将其消灭在萌芽状态,形成闭环安全管理.     

Risk assessment and risk reduction of an acrylonitrile production plant

Reducing accident occurrence in petrochemical plants is crucial, thus appropriately allocating management resources to safety investment is a vital issue for corporate management as international competition intensifies. Understanding the priority of safety investment in a rational way helps achieve this objective.In this study, we targeted an acrylonitrile plant. First, Dow Chemical's Fire and Explosion Index (F&EI) identified the reaction process as having the greatest physical risk. We evaluated the severity of accidents in the reaction process using the Process Safety Metrics advocated by the Center for Chemical Process Safety (CCPS); however, this index does not express damages a company actually experience. To solve this problem, we proposed a new metric that adds indirect cost to CCPS metrics. We adopted fault tree analysis (FTA) as a risk assessment method. In identifying top events and basic events, we attempted to improve the completeness of risk identification by considering accidents from the past, actual plant operation and equipment characteristics, natural disasters, and cyber-attacks and terrorist attacks. Consequently, we identified the top events with high priority in handling because of serious accidents as fire/explosion outside the reactor, fire/explosion inside the reactor, and reactor destruction. The new CCPS evaluation index proposed in this study found that fire and explosion outside the reactor has the highest severity. We considered the creation of the fault tree (FT) diagram of the top event, estimating the occurrence probability, and identifying the risk reduction part and capital investment aimed at risk reduction. As an economically feasible selection method for risk reduction investment, using the difference in loss amounts before and after safety investments indicated investment priority.     

Industrial accidents in spray dryer plants for dairy products in Europe

Despite the fact that the information about past accidents is an integral part of accident prevention, the information about industrial accidents is not commonly available in food and agricultural sectors. Spray dryer plants for dairy products are not an exception. The aim of this paper is the creation of the representative database for industrial spray drying accidents in order to identify their major causes. The paper is divided into 8 chapters. The first two chapters deal with the general information about technology of spray drying of dairy products. The third chapter provides the outputs from the authors' database containing records of 25 accidents in milk drying facilities in Europe. These accidents took place between 1999 and 2019 in six European countries. Based on the accident database, the most common causes of accidents were identified. Processes that can cause a fire, an explosion, or damage to environment are described in the fourth, fifth and sixth chapter. The seventh chapter deals with process, technical and organizational measures; these were discussed using literature research and the results of the accident database. The eighth chapter is the conclusion with a focus on further improvement of process safety through newly developed protective tools.     

特种设备安全监察地理信息系统设计

TS-GIS项目基于特种设备数据库系统和信息网络,以电子地图为背景,在监察机构对特种设备的动态监管中起到十分重要的作用,为地方政府在发生重特大事故时的紧急救援,及防范、控制和最大限度减轻特种设备特大和重大事故灾害提供了先进的技术手段,为企业对设备的运行监控、预警保障和安全生产提供了有力的支持.TS-GIS的建设为决策支持系统搭建基础网络平台和数据平台.本文对系统的设计思路、集成、数据库建设、应用开发等方面进行了较为详细的论述,并对系统下一步的建设作了技术上的探讨,为TS-GIS的建设提供了一套先进可行的技术手段,为特种设备安全监察地理信息系统的建设打下基础.     

Technical note on the contribution of sociotechnical factors to accidents notified to MARS

Not least due to the new `Seveso II Directive', Safety Management Systems (SMS) have become a hot topic in the `safety business'. To reveal in a structured way how organisations manage safety at their plants, classification schemes can be applied to identify plant-specific precautions on different hierarchical levels, e.g. from `top level' equipment reliability to `bottom level' safety climate. In this paper, such a model is used to classify the accidents reported to the European Commission's Major Accident Reporting System (MARS) according to the levels on which failures resulting in actual accidents did occur, and to cross-compare the levels of causation with the overall `severity' of the accidents. It is analytically shown that ∼66% of the accidents are caused by latent SMS failures, and that especially those accidents which are caused by failures in the `deepest layers of latency' have significantly higher `severities' than accidents caused by more `immediate' failures. In other words, it is quite likely that the deeper the underlying causes of an accident, the more `severe' its consequences. Implementing SMS is thus worth the effort.     

天津市安全生产现状及其分析研究

对天津市2000—2004年的工伤事故进行调查及统计,从工伤事故起数、事故死亡人数、重大伤亡事故、重点行业、事故类别等多个角度进行了分析研究,总结出天津市工伤事故发生的规律和特点;对照天津市及其重点行业的经济发展状况,对天津市的安全生产状况做出总体评价,指出了天津市的总体安全生产水平处于全国各省市的前列,列出了导致死亡事故的事故类别的排序。研究的成果,为制定从总体上控制天津市的工伤事故、不断提高安全生产水平的对策,提供了具有指导性的依据。     

A Bayesian network-based approach for the assessment and management of ageing in major hazard establishments

Currently, there is an increasing attention towards ageing of industrial equipment, as the phenomenon has been recognised as a cause of severe accidents, recorded in the last years in many process establishments. Recent studies described ageing through a number of key-factors affecting the phenomenon by accelerating or slowing it down. The Italian Competent Authority for the prevention of chemical accidents (Seveso III Directive) adopted a short-cut method, accounting for the assessment of these factors, to evaluate the adequateness of ageing management during inspections at Seveso sites. In this paper, a Bayesian Network was developed, by using the data gathered during the first application of the short-cut method, with the aim to verify the robustness of the approach for ageing assessment and the validity of the a priori assumptions used in assessing the key-factors. The structure of the Bayesian network was established by using experts’ knowledge, whereas the Counting Learning algorithm was adopted to execute the parameter learning by means of the software Netica. The results showed that this network could effectively explore the complex logical and uncertain relationships amongst factors affecting equipment ageing. Results of the present study were exploited to improve the short-cut method.     

Analysis of equipment failures as contributors to chemical process accidents

A database study of chemical process accident cases was carried out. The objective of the study is was to identify the reasons for equipment based accidents. The most frequent accident causing equipment were piping (25%), reactors and storage tanks (both 14%) and process vessels (10% of equipment accidents). The six most accident-prone equipment is process related involve nearly 80% of accidents.78% of equipment accident contributors are technically oriented including design and human/technical interface faults. Purely human and organizational reasons are the most common accident contributors for storage tanks (33%), piping (18%) and heat transfer equipment (16% of causes). For other equipment the technical accident causes are most common.The accident contributors were divided to main and sub-contributors. On average process equipment failures have 2.2 contributors. The contributors, which frequent and act often as main contributors, should be focused. These risky contributors were identified for several equipment types. Also a deeper analysis of the accident causes and their interconnections was made. Based on the analysis a checklist of main risk factors was created for hazard identification on different types of equipment.     

Korean experience of process safety management (PSM) regulation for chemical industry

From the 1960s, Korean industries have been encouraged by the government to nurture heavy and chemical industry and to modernize the economics and industrial structures. The development of chemical industry particularly became the turning point in industrial development, and played a major role in the construction of a new industrialized country. However, the process systems in the chemical industry have become more complex and larger, and the inventories of dangerous chemicals that are produced or consumed have continuously increased. Therefore, the hazards from potential accidents such as fire and explosion or release of toxic chemicals have also increased. In fact, from the end of 1980s to the beginning of 1990s in Korea, a number of major industrial accidents such as ABS extruder explosion, TDI release and dryer explosion, etc. Occurred and caused many fatalities. As the chemical companies recognized the importance of preventing major hazards, PSM system, the prevention of major industrial accidents, was introduced in January 1995 by amending Industrial Safety and Health Act, and it has been enforced from January 1, 1996. According to the law, the business owner of a workplace with hazardous or dangerous equipment shall submit a process safety report to the Government to prevent any accidents, which could inflict an immediate damage on workers or on areas in the vicinity of the workplaces. As a result of PSM implementation for 19 years, chemical accident prevention system has been stabilized and various kinds of effectiveness and desirable customer satisfaction have been made.     

2004—2017年浙江省较大以上生产安全事故统计分析

为充分探究浙江省生产安全事故发生规律,以2004—2017年浙江省生产安全事故为研究对象,从事故发生的时间关系、区域分布、行业分布、事故类型分布等方面对全省总体、工矿商贸领域、化工领域、典型危险作业4个分类的较大以上事故特点进行了剖析研究;并从政府监管的角度,提出事故防范的措施和建议。     

Ensuring emergency planning & response meet the minimum Process Safety Management (PSM) standards requirements

When incidents happen and the consequences are not mitigated effectively, one of the indicated failures consists of ineffective emergency planning and response (EPR). EPR is an important aspect of the Process Safety Management (PSM) Standards, and the guidelines are stated in CFR 1910.119 (n) which explains the minimum elements of emergency response and procedures in handling emergency or small releases. Despite its implementation in 1992, CSB finds ineffective EPR system in certain accidents such as the Missouri DPS Enterprise Chlorine Gas Release accident in 2002. DPS EPR failed in planning on location of emergency equipment and accessibility. Many other accidents have occurred throughout the decade and even though organizations have their own EPR system, there are issues in meeting minimum PSM requirements. There also exists the problem of self-regulatory policies practiced by organizations, which might not meet these requirements as well. To help organizations meet these minimum requirements, the purpose of this paper is to present a structured and easy technique to plan and implement EPR as per PSM requirements. A model has been developed based on this technique, and its application has been tested as a case study in a refinery in Malaysia and discussed throughout this report. The results reflected the feasibility of this model as it helped users to track and manage documents efficiently. This technique has the potential to help users to manage EPR better and to reduce adverse impacts to people, environment and assets.     

Prerequisites for learning from accident investigations – A cross-country comparison of national accident investigation boards

In this paper railway accident investigation reports issued by the national accident investigation boards in three Scandinavian countries during a 2-year period have been systematically studied. Content analysis of attributed causes in these reports reveals a considerable emphasis on physical processes, actor activities and equipment (the microlevel). Much less attention is paid to organisational factors (the mesolevel) and conditions related to regulators, associations and government (the macrolevel). This means that lessons will primarily be learned about aspects at the lower of these levels. Interviews show that the factors emphasised in investigation reports typically reflect the competences and experiences of the investigators, i.e. they are inclined to focus on areas of their own expertise. Since failures at the microlevel in many cases merely are symptoms of trouble at higher levels, it is argued that competence among investigators that supplements entirely technical or operational backgrounds are necessary for enabling deeper understanding of the factors leading to accidents. One possible way for achieving this is the creation of multi-modal investigation boards that provide a number of potential advantages, such as increased access to specialist competences that are shared between different sectors. Although a multi-modal approach to some degree has been adopted in all three countries, interviews reveal that these positive effects do not emerge automatically. It can therefore be concluded that multi-modal investigation boards offer a number of possible advantages, but only when these synergies are fully exploited can they provide a potential for more effective learning from accidents.     

Fuzzy risk modeling of process operations in the oil and gas refineries

Operating several assets has resulted in more complexity and so occurrence of some major accidents in the refining industries. The process operations risk factors including failure frequency and the consequence components like employees' safety and environment impacts, operation downtime, direct and indirect cost of operations and maintenance, and mean time to repair should be considered in the analysis of these major accidents in any refinery. Considering all of these factors, the risk based maintenance (RBM) as a proper risk assessment methodology minimizes the risk resulting from asset failures. But, one of the main engineering problems in risk modeling of the complex industries like refineries is uncertainty due to the lack of information. This paper proposes a model for the risk of the process operations in the oil and gas refineries. The fuzzy logic system (FLS) was proposed for risk modeling. The merit of using fuzzy model is to overcome the uncertainty of the RBM components. This approach also can be accounted as a benchmark for future failures. A unified risk number would be obtained to show how the criticality of units is. The case study of a gas plant in an oil refinery is performed to illustrate the application of the proposed model and a comparison between the results of both traditional RBM and fuzzy method is made.For the case study, 26 asset failures were identified. The fuzzy risk results show that 3 failures have semi-critical level and other 23 failures are non-critical. In both traditional and fuzzy RBM methods, some condenser failures had the highest risk number and some pumps were prioritized to have the lowest risk level. The unit with unified risk number less than 40 is in the non-critical conditions. Proposed methodology is also applicable to other industries dealing with process operations risks.     

Driver Fatigue and Road Safety on Poland’s National Roads

This paper presents an overview of factors causing driver fatigue as described in the literature. Next, a traffic crash database for 2003–2007 is used to identify the causes, circumstances and consequences of accidents caused by driver fatigue on Poland’s national roads. The results of the study were used to build a model showing the relationship between the concentration of road accidents and casualties, and the time of day. Finally, the level of relative accident risk at night-time versus daytime is defined. A map shows the risk of death and severe injury on the network of Poland’s national roads. The paper suggests to road authorities steps to reduce fatigue-related road accidents in Poland.     

Study of the severity of industrial accidents with hazardous substances by historical analysis

This paper studies the levels of risk in industrial facilities where hazardous substances are used, evaluating the influence of certain variables on the severity of the accidents that have occurred until now. It makes use of the incidents recorded in the July 2001 version of the MHIDAS database. This study reveals that accidents in developed countries are less severe than those that occur in other geographical areas. Also, it establishes the influence on the severity (number of fatalities) of this kind of incident of certain factors: the type of incident and the type and amount of substance involved. Lastly, the extent to which current facilities comply to the risk tolerance criteria in various countries is evaluated with regards to incidents involving explosions.     

Operational risk assessment of chemical industries by exploiting accident databases

Accident databases (NRC, RMP, and others) contain records of incidents (e.g., releases and spills) that have occurred in the USA chemical plants during recent years. For various chemical industries, [Kleindorfer, P. R., Belke, J. C., Elliott, M. R., Lee, K., Lowe, R. A., & Feldman, H. I. (2003). Accident epidemiology and the US chemical industry: Accident history and worst-case data from RMP*Info. Risk Analysis, 23(5), 865–881.] summarize the accident frequencies and severities in the RMP*Info database. Also, [Anand, S., Keren, N., Tretter, M. J., Wang, Y., O’Connor, T. M., & Mannan, M. S. (2006). Harnessing data mining to explore incident databases. Journal of Hazardous Material, 130, 33–41.] use data mining to analyze the NRC database for Harris County, Texas.Classical statistical approaches are ineffective for low frequency, high consequence events because of their rarity. Given this information limitation, this paper uses Bayesian theory to forecast incident frequencies, their relevant causes, equipment involved, and their consequences, in specific chemical plants. Systematic analyses of the databases also help to avoid future accidents, thereby reducing the risk.More specifically, this paper presents dynamic analyses of incidents in the NRC database. The NRC database is exploited to model the rate of occurrence of incidents in various chemical and petrochemical companies using Bayesian theory. Probability density distributions are formulated for their causes (e.g., equipment failures, operator errors, etc.), and associated equipment items utilized within a particular industry. Bayesian techniques provide posterior estimates of the cause and equipment-failure probabilities. Cross-validation techniques are used for checking the modeling, validation, and prediction accuracies. Differences in the plant- and chemical-specific predictions with the overall predictions are demonstrated. Furthermore, extreme value theory is used for consequence modeling of rare events by formulating distributions for events over a threshold value. Finally, the fast-Fourier transform is used to estimate the capital at risk within an industry utilizing the frequency and loss-severity distributions.