Monte Carlo Method-Based Behavioral Reliability Analysis of Fully-Mechanized Coal Mining Operators in Underground Noise Environment

Zhu

et al. 2022

Front. Public Health

The risk factors affecting workers' unsafe acts were comprehensively identified by Human Factors Analysis and Classification System (HFACS) and grounded theory based on interview data and accident reports from deep coal mines. Firstly, we collected accident case and field interview data from deep coal mines issued by authoritative institutions. Then, the data were coded according to grounded theory to obtain relevant concepts and types. The HFACS model was used to classify the concepts and categories. Finally, the relationship between core and secondary categories was sorted out by applying a story plot. The results show that risk factors of unsafe acts of deep coal mine workers include environmental factors, organizational influence, unsafe supervision and unsafe state of miners, and the main manifestations of unsafe acts are errors and violations. Among them, the unsafe state of miners is the intermediate variable, and other factors indirectly affect risky actions of coal miners through unsafe sates. Resource management, organizational processes and failure to correct problems are the top three risk factors that occur more frequently in unsafe acts. The three most common types of unsafe act are unreasonable labor organization, failure to enforce rules, and inadequate technical specifications. By combining grounded theory and the HFACS framework to analyze data, risk factors for deep coal miners can be quickly identified, and more precise and comprehensive conceptual models of risk factors in unsafe acts of deep coal miners can be obtained.

“…In addition, it clarifies the mechanism of risk factors on unsafe acts. Therefore, our findings provide a starting point for more detailed research in the future ( 34 , 35 ).…”

Section: Discussionmentioning

confidence: 66%

Risk Factors Identification of Unsafe Acts in Deep Coal Mine Workers Based on Grounded Theory and HFACS

Yang

Zhu

et al. 2022

Front. Public Health

“…In this paper, we focus on the reliability assessment of human in the system, and the results obtained are slightly different from the past studies. Past studies have concluded that environmental factors 20 , 47 , human emotions, and some physiological abnormalities 48 have a greater impact on the reliability of human factors in coal mine production. In this study, we found through BN reasoning analysis that the complexity of tasks and the design of human–machine interface in smart coal mines more affect the human factor reliability of human in human–computer interaction system.…”

Section: Discussionmentioning

confidence: 99%

“…They analyze how human activity affects safety and reliability systems using systems engineering and cognitive and behavioral sciences, and they forecast the likelihood of human errors based on employee actions and decisions. In the study of human reliability in the field of coal mining, Wang et al 20 analyzed the behavioral reliability of traditional mechanized coal mining operators using Monte Carlo methods. The influence of sound in the working environment on the behavioral reliability of operators was explored, but the influence of human own factors on behavioral reliability was ignored.…”

Section: Introductionmentioning

confidence: 99%

Human reliability assessment of intelligent coal mine hoist system based on Bayesian network

Sun

et al. 2022

Sci Rep

The human reliability of intelligent coal mine hoist operation system is affected by many factors, in order to reduce the occurrence of human error in the hoist system and improve the reliability of the system. The characteristics of phased-mission task operation of hoists is combined, the phase dependence of human cognitive errors is considered and, a new human reliability evaluation method is proposed with the help of Bayesian network (BN) model in this paper. Firstly, the phase dependence of human cognitive errors was analyzed based on the cognitive behavior model. Then the human error analysis in the hoist system was carried out, and several main performance shaping factors are selected. Secondly, BN was used to build the human reliability model of the hoist system at each stage. Finally, it is found that the phase dependence of cognitive errors has a negative impact on the human reliability of the hoist system through the case analysis. At the same time, several main performance shaping factors (PSFs)were quantitatively analyzed by using the reverse reasoning ability of BN, which proves the effectiveness of the proposed method, and provides a scientific and reasonable theoretical basis for the development of effective human error prevention measures for the operation of intelligent coal mine hoists.

“…Chi et al ( 61 ) also found that working conditions (such as working face conditions and weather) were closely related to workers' behaviors, accident types, and the degree of accident injuries through the analysis of safety accidents in doctoral dissertations in the United States during 2002–2011. Yoon et al ( 68 , 69 ) pointed out that a strong noise environment seriously affects the physical and mental health of operators and leads to unsafe behaviors of workers. On the contrary, Lu et al ( 70 ) proposed that pleasant sounds can help workers learn safe behaviors and effectively reduce unsafe behaviors.…”

Section: Literature Reviewmentioning

confidence: 99%

Influencing Factors, Formation Mechanism, and Pre-control Methods of Coal Miners′ Unsafe Behavior: A Systematic Literature Review

Yang

Zhu

et al. 2022

Front. Public Health

Coal mine accidents are mainly caused by the unsafe behavior of workers. Studying workers' unsafe behaviors can help in regulating such behaviors and reducing the incidence of accidents. However, there is a dearth of systematic literature review in this area, which has hindered mine managers from fully understanding the unsafe behavior of workers. This study aims to address this research gap based on the literature retrieved from the Web of Science. First, a descriptive statistical analysis is conducted on the year, quantity, publications, and keywords of the literature. Second, the influencing factors, formation mechanism, and pre-control methods of coal miners' unsafe behavior are determined and discussed, and the research framework and future research directions of this study are proposed. The study results will help mine safety managers fully understand the influencing factors, formation mechanism, and pre-control methods of workers' unsafe behavior, and lay a theoretical foundation for the future research direction in this field.