The role of behavioral factors on safety management in underground mines

Traditional approaches on the prevention of accidents/injuries in mines reached its limit of effectiveness in improving safety performance and a fresh approach is utmost required. Behavioral safety analysis has been identified as an effective alternative in many industries. This paper is therefore sought to examine the role of behavioral factors on the occurrence of mine accidents and injuries through a case study. Data were collected from two neighboring underground coalmines operating under a large public sector organization of India. High–low plots and t-test were done to explore the differences between behavioral characteristics of accident involved (case) and non-involved (control) workers. How these differences could cause accidents/injuries in mines was estimated through structural equation modeling. The case study results show that accident group of workers (cases) are more job dissatisfied, negatively affected, and highly risk taking compared to the non-accident group of workers (controls). The accident model path analysis shows that negative affectivity, job dissatisfaction, and risk taking behaviors predict an increased number of injuries in mines. Apart from direct influences to work injuries, negative affectivity and job dissatisfaction make workers to take more risks and behave unsafely. These findings contribute to the design of safety programs including safety training, which should be behaviorally motivated. Mine safety management of the case study mines should outskirt their age old belief that accidents/injuries are due to hazardous nature of mining and only engineering control and regulatory monitoring are sufficient for improving safety of the mines. The multivariate analysis also shows that experience bears no relationships with work injury indicating that a less experienced worker is equally likely to be injured as an experienced worker. It implies that experience though helps workers in understanding the physical hazards, however, avoiding the imminent danger is much more behavioral. The variables negative affectivity, job dissatisfaction, and risk taking behaviors are therefore crucial in avoiding accident/injuries in mines.     

Factors associated with occupational injury severity in the New South Wales underground coal mining industry

The relationship between a large number of mine and mine worker characteristics and injury severity was examined using multiple regression techniques. The study was based on data extracted from the New South Wales (N.S.W.) Joint Coal Board's computer based accident/incident reporting system describing 21,372 non-fatal, lost-time injurious incidents that occurred in the N.S.W. underground coal mining industry during the 4 year period from 1 July 1986 to 30 June 1990. The number of days lost as a result of an injurious incident was the best available proxy measure of injury severity. Over the study period, the number of days lost per 100,000 tonnes of raw coal production declined by 73%. Over the same period, injurious incidents involving more than 20 days off work, which constituted only 16% of all injurious incidents in underground mines, resulted in 75% of the total days lost for the whole N.S.W. underground coal mining industry. Factors that had practical importance and that were significantly associated with injury severity included mine worker's age, part of the body injured, type of accident, agency of accident, and mine worker activity. Factors not important or not significant in their relationship with injury severity were: time into shift, previous hours worked, mine location of incident, occupation, work experience, frequency of task, shift, and mining region. This study suggests that factors related to the susceptibility of a mine worker's body tissue to damage or repair, and factors related to the concentration of energy on the mine worker by vehicle and environmental characteristics are important determinants of injury severity.     

地下采矿安全信息管理系统开发与应用

地下矿床开采潜在着众多的事故隐患，因此，为了进行事故隐患预防和预测，进行矿山安全信息管理和事故分析就显得十分重要。针对金川矿区的地质、采矿条件，研究开发了集“安全信息管理与事故分析”于一体的计算机辅助系统。简要地介绍了该系统的功能、作用以及应用情况。     

Off-road truck-related accidents in U.S. mines

IntroductionOff-road trucks are one of the major sources of equipment-related accidents in the U.S. mining industries. A systematic analysis of all off-road truck-related accidents, injuries, and illnesses, which are reported and published by the Mine Safety and Health Administration (MSHA), is expected to provide practical insights for identifying the accident patterns and trends in the available raw database. Therefore, appropriate safety management measures can be administered and implemented based on these accident patterns/trends.MethodsA hybrid clustering-classification methodology using K-means clustering and gene expression programming (GEP) is proposed for the analysis of severe and non-severe off-road truck-related injuries at U.S. mines. Using the GEP sub-model, a small subset of the 36 recorded attributes was found to be correlated to the severity level.ResultsGiven the set of specified attributes, the clustering sub-model was able to cluster the accident records into 5 distinct groups. For instance, the first cluster contained accidents related to minerals processing mills and coal preparation plants (91%). More than two-thirds of the victims in this cluster had less than 5 years of job experience. This cluster was associated with the highest percentage of severe injuries (22 severe accidents, 3.4%). Almost 50% of all accidents in this cluster occurred at stone operations. Similarly, the other four clusters were characterized to highlight important patterns that can be used to determine areas of focus for safety initiatives.ConclusionsThe identified clusters of accidents may play a vital role in the prevention of severe injuries in mining. Further research into the cluster attributes and identified patterns will be necessary to determine how these factors can be mitigated to reduce the risk of severe injuries.Practical applicationAnalyzing injury data using data mining techniques provides some insight into attributes that are associated with high accuracies for predicting injury severity.     

倾斜井巷轨道运输事故的系统安全分析

在诸多煤矿发生的事故中 ,除一些恶性事故外 ,大部分伤亡事故属于运输事故。运输事故是煤矿三大事故之一 ,其对矿井的安全生产构成了严重威胁。笔者以倾斜井巷轨道运输事故为研究对象 ,利用系统安全分析方法中的 FTA(事故树分析法 )进行了定性分析和定量计算 ,寻找事故发生的原因 ,从而有的放矢地采取安全对策 ,以减少事故的发生。     

Underground coal mining injury: A look at how age and experience relate to days lost from work following an injury

Coal has been mined in the United States since colonial times and coal mining has always been a dangerous occupation. Despite the dangers involved in coal mining, coal is essential to the functioning of our society. Coal provides energy for products, businesses, and homes. Not only is coal mining a dangerous occupation, but, like many other industries, coal mining has also been referred to as a “graying occupation” as many coal miners are reaching retirement age. Younger workers possess certain advantages as older workers may have age-associated decrements in cognitive function, health, and recuperative ability. Although there are documented decreases in health and safety associated with age, there are also benefits at the workplace associated with increasing age. Increasing age brings about more experience and familiarity with the work environment. This study used the Mine Safety and Health Administration’s (MSHA) database on accidents, injury, and illness from the years 2003 through 2007 to examine how age, experience at the current mine, total years experience as a coal miner, and experience in the current job affects injury severity. The results of the data indicated that there was a relationship between age and days lost as well as total mining experience and days lost following an injury. Furthermore, the data indicated an increased risk of overexertion injuries as age increases. These are important findings for the coal mining industry as many miners are more experienced and older.     

基于贝叶斯网络的煤矿事故人因推理

煤矿事故的不可重现性决定了事故原因的调查具有很强的不确定性,如何通过事故发生后的相关信息提高事故深层次原因调查的准确性是非常重要的。将HFACS与贝叶斯网络相结合,以煤矿事故HFACS分析结果为样本,通过卡方检验和让步比分析建立人因的贝叶斯网络因果图,进一步利用最大似然估计算法确定了煤矿事故人因的贝叶斯网络参数。最后,以双柳煤业顶板事故的调查信息为证据推理导致煤矿事故发生的深层次原因,提高事故原因调查的准确性,从而验证模型的有效性。     

Logistic regression model for prediction of roof fall risks in bord and pillar workings in coal mines: An approach

The roof fall hazards are the major problems in underground coal mines, which are generally unpredictable due to the associated uncertainties arising out of the complexity of geological conditions and variability in mining parameters. During the six year period, 1996–2001, 253 Indian coal miners lost their lives and 401 are seriously injured in 490 different roof fall accidents. In India, 32.7% of the total fatal injuries in coal sectors are due to roof fall in bord and pillar method of workings. This paper attempts to predict the severities of roof fall accidents based on some major contributing parameters using the binary logistic regression model. In total, 128 roof fall accidents for the last few years from five underground coal mines in India having bord and pillar method of working are analyzed for this study. The results revealed that wider gallery width is more prone to major and serious accidents than narrower gallery width. Thin seams are more amenable to major accidents in comparison to thick seams. Unsupported or partially supported roofs have higher risk for contributing major as well as serious accidents. Deep workings are more prone to major accidents as compared to shallow depth workings.     

基于数据挖掘的化工生产事故致因主题抽取

为充分挖掘化工生产事故数据中的有效信息和潜在规律,提高对化工事故认知水平,针对某化工集团2010—2016年共1 578起事故数据,利用社会网络分析等方法揭示事故要素间的关联关系;运用潜在狄利克雷分配（LDA）模型进行事故聚类,并抽取到5个事故致因主题。研究结果表明:LDA主题模型等数据挖掘技术能有效挖掘大量事故数据中的潜在信息;5个事故致因主题中,4个涉及到人因或组织层面的缺陷;员工注意力不集中和现场风险管理不足这2个致因主题间具有较强相关性;员工注意力不集中、现场风险管理不足以及设备问题是导致事故发生的主要原因。     

基于层次话题模型的煤矿安全事故致因要素研究

为促进安全发展,强化煤矿安全管理的科技支撑,在事故致因理论基础上,利用文本挖掘中的话题模型和创新性构建的层次致因要素话题模型,对我国2000—2015年发生的386起重特大煤矿事故调查报告进行了深入地挖掘、分析和研究。发现事故致因隐含的规律及各类事故之间的关联与共性,并进一步研究发现不同致因要素随时间的演化规律及致灾倾向,为煤矿安全管理找出重点,指导煤矿安全生产管理实践。     

某地下矿山安全生产事故规律分析与对策研究

基于某地下矿山2000-2009年度所发生的安全生产事故的详细统计数据,分别针对伤害程度、伤害部位、事故工龄、事故班次、事故致因和类别等进行了全面统计、归纳和分析,并采用事故树等分析法对冒顶片帮和人为原因引发的两类重要矿山事故进行了深入系统研究,确定了矿山典型事故发生的基本原因、主导控制因素、一般出现规律以及可能伤害后果。结合工程实际情况,提出了能有效降低生产事故频率,提高安全生产效率的四种具体对策与措施：（1）加强安全教育与技能培训,提高员工安全法制意识和应对突发事故的专业能力;（2）遵守人机工效学的一般原理,改善工作舒适度,提高员工工作积极性和效率;（3）坚持科学发展观,采用合理的先进生产工艺和现代化管理措施;（4）加强劳动保护用品的科学使用与人性化管理。研究成果具有重要的推广应用价值。     

系统安全相似分析法及其应用

系统安全相似分析法是发掘共性事故致因,运用逻辑学和数学方法解决安全问题的方法。通过评价比较分析法、比较安全法、模糊相似分析法与系统相似分析法的优缺点,采用多隶属模糊集对系统相似分析法进行改进,克服其无法度量模糊因素相似性的缺陷,得到适用于模糊系统的系统安全相似分析法。基于此,建立系统安全相似度计算数学模型,并构建系统安全相似分析范式。将改进的分析方法应用于4起典型煤矿瓦斯爆炸事故,分析得出,越界开采、井下密闭作业、应急救援不力、密不上报、拒不撤出作业人员等是造成瓦斯爆炸事故严重程度升级的主要因素;物质流、能量流、信息流相似度接近于1,然而其对造成事故的潜在影响受到忽视,是煤矿避免瓦斯爆炸事故的极佳着手点。结果表明,这一改进有效实现了事故致因因素的相似性度量,为系统安全分析与事故预防提供了新思路与新方法。     

Development of a relative risk model for roof and side fall fatal accidents in underground coal mines in India

A relative risk model for roof and side fall fatal accidents was developed using loglinear analysis of two-way contingency table. A few statistics such as potential fatalities (PF), relative risk of fatalities (RRF) and safety measure effectiveness (SME) were derived which can be used as key safety performance indicators of roof and side fall accidents in underground mines. The model was applied to large roof and side fall fatal accident data for a period of 6-years occurred in six companies involving 292 underground coal mines. The application reveals that effectiveness of safety measures across different locations in underground mines varies and focus is mainly concentrated in highly populated workplaces such as face. The model and the statistics developed in this study are generic and can be applied to any industrial setting.     

近年来山西省煤矿事故特点及对策措施

为掌握近年来山西省煤矿事故的发生特点,基于2015年—2018年山西省煤矿事故数据并结合全国煤矿事故数据进行对比,对事故等级、类型、地点、企业性质、煤矿辖区5个维度进行统计分析。结果表明:煤炭价格与煤矿安全形势有正负影响;近年来山西省煤矿安全总体形势好于全国,但机电、运输事故频发,水害事故时有发生,需要对该类事故加强防范措施;回采工作面为事故多发地点,这与全国煤矿事故特点不尽相同;国有重点煤矿的事故起数、死亡人数均高于地方煤矿企业,这主要是由于国有重点煤矿数量多、产量大的原因。应同时努力提高员工素质,坚决落实安全责任制,实现煤矿企业的安全生产。     

Risk assessment: an approach to control hazards in mines

Accidents and injuries related to work are major occupational health problems in most of the industrialized countries.Traditional approaches to manage workplace safety in mines have mainly focused on job redesign and technical aspects of engineering systems.It is being realized that compliance to rules and regulations of mines is a prerequisite;however,it is not sufficient to achieve further reduction in accident and injury rates in mines.Proactive approaches are necessary to further improve the safety standards in mines.Unsafe conditions and practices in mines lead to a number of accidents,which in turn may cause loss and injury to human lives,damages to property,and loss of production.Hazard identification and risk assessment is an important task for the mining industry which needs to consider all the risk factors at workplaces.Applications of risk management approaches in mines are necessary to identify and quantify potential hazards and to suggest effective solutions.In this paper,the following risk estimation techniques were discussed:(i)DGMS(Directorate General of Mines Safety,India)risk rating criterion,and(ii)a matrix based approach.The proposed tools were demonstrated through an application in an opencast coal mine in India.It was inferred that the risk assessment approach can be used as an effective tool to indentify and control hazards in mines.     

Analysis of work related accidents in the Spanish mining sector from 1982-2006

Introduction

The rate for work related accidents in the Spanish mining sector is notably higher than in other countries such as the United States. It produces a very negative impact on the mining industry. This paper is the report of a study on serious and fatal accidents in Spanish mining from 1982-2006. It is based on the reports of 212 accidents (serious or fatal) carried out by the General Management of Energy and Mining of Catalonia (Spain). Method: The high work-related accident rate in the Spanish mining sector makes it necessary to carry out an analysis and research that can shed light on the causes of this high rate; this is the only way that a solution can be found. The study is based on Feyer and Williamson's analysis of accident causes, as they apply to 212 accidents. The types and causes of the accidents are coded according to the coding system used by the Spanish National Institute for Safety and Hygiene in the Workplace, which allows us to identify a series of direct causes and contributing factors in different accidents. Results If all the causes and factors that are present in the accidents are known, we are able to look for appropriate solutions to reduce them as much as possible. In short, we are able to come up with a series of conclusions that expose the weak links in the management of accident prevention in companies. This is helpful in the struggle to reduce work injuries in the Spanish mining sector.     

基于文本挖掘和复杂网络的事故致因重要度评估方法——以房屋市政较大以上事故为例

为充分挖掘事故调查报告中的有效信息,明确安全管理工作的内容.首先,利用文本挖掘分析事故调查报告,采用最小词频阈值文档频改进信息增益评估函数对分词结果降噪,通过回溯特征项在报告中的具体表述,提取事故致因,再构建同义词词库.然后,引入复杂网络以改进TF-IDF,综合事故致因因素的关联特征评估其重要度.最后,以房屋市政较大及...     

煤矿瓦斯事故危险源分类及其耦合作用分析

近年来,我国煤矿瓦斯事故频发,瓦斯事故的发生不仅造成了巨大的经济损失而且产生了不良的社会影响。但是煤矿瓦斯事故的发生并不是单一因素作用的结果,而是多种因素相互作用、相互影响,从而导致瓦斯事故的发生。这就要求我们对煤矿瓦斯事故危险源进行合理的分类,并在此基础上进行多危险源间的耦合作用分析。因此,具体全面的对瓦斯事故危险源进行分类且对其耦合作用进行分析,对丰富多因素相互作用理论,深入对煤矿系统的分析具有重要的理论意义。     

Association analysis of accident factors in petrochemical storage tank farms

In order to identify and clarify the association between the factors leading to accidents in a petrochemical tank area, this study analyzes investigation reports of 212 petrochemical tank farm accidents and combines this with the “association rule” mining and science related to complex networks. The main risk factors are determined and a risk factor data set is constructed; 75 association rules are extracted from the factor data set based on the Apriori algorithm. Then the obtained association rules are used to construct an accident factors network of the petrochemical storage tank area, and the topology characteristics of the network are further analyzed to reveal the importance of factors. Factors with large node degree, betweenness, and clustering coefficients are obtained, such as “violation of operating regulations”, “high concentration of flammable gas in the air”, “lack of experience and professional skills”, etc. These factors play an important role in the formation and development of accidents. The results also show that the accident cause network of the petrochemical storage tank area has a small average shortest path length and a large cluster coefficient, indicating a relatively close connection between the accident factors. The contributions of this study is not only extracting the hidden relationships among contributory factors to tank farm accidents using association analysis, but also revealing which factors are more important for the tank farm safety through the complex network.     

Status and future tasks of coal mining safety in China

In general, contexts of coal mining safety involve technology, administration and socioeconomic environment as well. This paper presents statistical analysis of China coal mine accidents in recent years and analyzes the reasons causing coal mining high risk from technical and socioeconomic viewpoints. Social and economic reform has been unleashing social, economical factors that are driving a fundamental transformation of new workplace safety problems and making China coal mining safety take on Chinese features. Compared with major state-owned and local state-owned coalmines, township and village coalmines are most dangerous coal mines with highest occupational risks. The incidence and death toll of ceiling accidents are higher than those of accidents such as gas, machinery, electricity, transportation, flood, and fire. New organizational risks appeared with rapid development of state-owned coal mines’ reorganization. Low skilled labors restrict both technical renovation and safety management. The Government has adopted a systematic arrangement to improve coal mining safety such as closing the township and village coalmines that cannot meet the standard of safety, reinforcing the supervision over coal mining safety, strengthening technological renovation and enhancing work safety input.