Analysis 320 coal mine accidents using structural equation modeling with unsafe conditions of the rules and regulations as exogenous variables

Zhang, Yingyu; Shao, Wei; Zhang, Mengjia; Li, Hejun; Yin, Shuiqing; Xu, Yang

doi:10.1016/j.aap.2016.02.021

Cited by 106 publications

(75 citation statements)

References 56 publications

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“…procedures. These statements are in accordance with [36], who studied 320 underground mines and 224 concluded that the three most influencing factors of coal mine accidents are: 1) lack of safety 225 education and training, 2) rules and regulations of safety production responsibility and 3) rules and 226 regulations of supervision and inspection.…”

supporting

confidence: 51%

Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data Mining Techniques

Pera¹,

Bascompta²,

Rossell³

et al. 2018

Preprint

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supporting

confidence: 51%

Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data Mining Techniques

Pera¹,

Bascompta²,

Rossell³

et al. 2018

Preprint

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“…Although most systems approaches consider accidents to be the outcome of the interactions between various system components, an appealing view is that interactions cannot be predicted due to system complexity (e.g., Larsson et al, ; Leveson, ; Skyttner, ), as well as provide grounds to perform an accurate calculation or measurement of the strength or size of the relationships. Zhang et al () applied a systems analysis approach using structural equation modelling to quantitatively investigate the relationships between the factors that contribute to coal mining accidents. Specifically, the interactions between exogenous variables (unsafe conditions of the rules and regulations) and endogenous variables were discovered, including unsafe conditions of the equipment, unsafe behaviours of operators, and unsafe environmental conditions.…”

Section: Discussionmentioning

confidence: 99%

Contributory factors interactions model: A new systems‐based accident model

et al. 2019

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Understanding the interactions between contributory factors associated with accidents is important. However, the widely applied Swiss cheese model (SCM) and the human factors analysis and classification system (HFACS) oversimplify the causes of accidents and ignore the interactions among the various components of an entire system, which is the essence of systems thinking. A new systems‐based accident model that reflects the nature of the accidents and can be explained by the underlying accident model must therefore be developed. This study aims to create a new accident model that represents the interactions between the contributory factors, which can offer a systems approach to conducting a comprehensive examination of accidents. We use data obtained from the official accident reports on 94 extraordinary major coal mining catastrophes that took place from 1997 to 2011 in China. The results reveal that all latent conditions, including external factors, organizational influences, unsafe supervision, and preconditions for unsafe behaviours can influence active failures, that is, unsafe behaviours. However, only the preconditions for unsafe behaviours can influence unsafe behaviours within the SCM and HFACS frameworks. Furthermore, latent conditions can affect each other within the contributory factors interactions model. This study provides a new systems‐based accident model that allows us to examine and explain the relationships and linkages within and between complex sociotechnical systems and identify the common factors and interactions that cross human, external, and organizational factors.

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“…Coal mining is also considered one of the most dangerous jobs in the world [3]. Compared with other industries, coal mine workers face a relatively more dangerous working environment [4]. The frequent occurrence of coal mine accidents seriously affects the security situation of China’s coal industry and the sustainable development of the whole society’s economy [5].…”

Section: Introductionmentioning

confidence: 99%

Characteristic Analysis of Unsafe Behavior by Coal Miners: Multi-Dimensional Description of the Pan-Scene Data

Tong

Zhang

Pengcheng

et al. 2018

IJERPH

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As a high-risk occupation, coal mining has many accidents, primarily due to the unsafe behavior of coal miners. Based on the research of analysis of unsafe behavior and pan-scenario data of miners, a theoretical framework for the analysis of unsafe behavior characteristics was proposed in this paper. The collected data were divided into realistic scenes and abstract scenes according to different manifestations; the pan-scene data were described from the eight dimensions of time, behavioral trace, location, behavioral property, behavioral individual, degree, unsafe action, and specialty using a quantitative method for the structure conversion; and the rules were discovered through cluster analysis and association analysis. A total of 225 coal mine gas explosion accidents were used for analysis, and the pan-scene data description and structure conversion of unsafe behavior that caused these accidents were realized. In a certain cluster, the distribution rules of dimensions and the interaction between different dimensions of unsafe behavior were explored after analysis. The results show that the proposed eight dimensions can fully explain the basic characteristics and attributes of the unsafe behavior of coal miners. The structure conversion can reduce the workload of managers and effectively improve the safety data processing capabilities, and the result of data analysis can provide data support and a management basis for safety management. A new method and thought for the data analysis of miners’ unsafe behavior is provided.

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Analysis 320 coal mine accidents using structural equation modeling with unsafe conditions of the rules and regulations as exogenous variables

Cited by 106 publications

References 56 publications

Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data Mining Techniques

Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data Mining Techniques

Contributory factors interactions model: A new systems‐based accident model

Characteristic Analysis of Unsafe Behavior by Coal Miners: Multi-Dimensional Description of the Pan-Scene Data

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