A Methodology for Dynamic Assessment of Laboratory Safety by SEM-SD

The unsafe behavior of miners seriously affects the safety of deep mining. A comprehensive evaluation of miners’ unsafe behavior in deep coal mines can prevent coal mine accidents. This study combines HFACS-CM, SEM, and SD models to evaluate miners’ unsafe behaviors in deep coal mining. First, the HFACS-CM model identifies the risk factors affecting miners’ unsafe behavior in deep coal mines. Second, SEM was used to analyze the interaction between risk factors and miners’ unsafe behavior. Finally, the SD model was used to simulate the sensitivity of each risk factor to miners’ unsafe behavior to explore the best prevention and control strategies for unsafe behavior. The results showed that (1) environmental factors, organizational influence, unsafe supervision, and unsafe state of miners are the four main risk factors affecting the unsafe behavior of miners in deep coal mines. Among them, the unsafe state of miners is the most critical risk factor. (2) Environmental factors, organizational influence, unsafe supervision, and the unsafe state of miners have both direct and indirect impacts on unsafe behaviors, and their immediate effects are far more significant than their indirect influence. (3) Environmental factors, organizational influence, and unsafe supervision positively impact miners’ unsafe behavior through the mediating effect of miners’ unsafe states. (4) Mental state, physiological state, business abilities, resource management, and organizational climate were the top five risk factors affecting miners’ unsafe behaviors. Taking measures to improve the adverse environmental factors, strengthening the organization’s supervision and management, and improving the unsafe state of miners can effectively reduce the risk of miners’ unsafe behavior in deep coal mines. This study provides a new idea and method for preventing and controlling the unsafe behavior of miners in deep coal mines.

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“…The contribution rate (

) was defined in this study to measure the sensitivity of each risk factor to the level of unsafe behavior of miners. The

value is calculated as follows [ 65 ]:

…”

Section: Resultsmentioning

confidence: 99%

Comprehensive Evaluation of Deep Coal Miners’ Unsafe Behavior Based on HFACS-CM-SEM-SD

Yang

Wang

Zhu

et al. 2022

IJERPH

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“…In addition, we needed to normalize the coefficients of system dynamics equation in the simulation model; the results are shown in Table 2 [ 27 ].…”

Section: Simulating and Results Analysismentioning

confidence: 99%

“…System dynamics is based on feedback loops; therefore, it is insensitive to most non-critical parameters in the model. As long as the parameter estimation is within a reasonable range, there will be little or no deviation in the model results [ 27 ]. Therefore, the influence of the error term σ i ( i = 1, 2, … n ) was not considered in this study, and its value was set to 0, the same as below.…”

Section: Methodsmentioning

confidence: 99%

Dual-Attitude Decision-Making Processes of Construction Worker Safety Behaviors: A Simulation-Based Approach

Zhou

Chen

et al. 2022

IJERPH

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Workplace accidents are of great concern in the construction industry. Most of those accidents are caused by unsafe behavior in the workplace. Many previous studies have analyzed the causes of workers’ unsafe behaviors, but few have investigated workers’ feelings of insecurity from the perspective of systematic psychological theory. This study developed an attitude–behavior–intervention feedback loop mechanism of construction workers and used the dual-attitude theory to explain the occurrence mechanisms of unsafe behavior. Using this mechanism, an active-intervention system-dynamics model and a passive-intervention system-dynamics model were designed and simulated. The coefficient of the system dynamics equation in the simulation model involved meta-analysis to combine the correlation coefficients of existing studies, which increased the sample size and improved the statistical test efficiency. The results show that an implicit safety attitude has a more significant impact on safety behavior, and the effect of an active intervention is stronger than that of a passive intervention. Based on these results, this paper presents some feasible suggestions to reduce the probability of unsafe worker behaviors occurring.

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“…To convert qualitative linguistic expressions to corresponding fuzzy numbers, Chen and Hwang established a relationship between qualitative terms and their corresponding fuzzy numbers in different scales [ 56 ], which enables the transformation of subjective judgements and linguistic expressions into measurable and numerical data. As to the number of verbal expressions, five verb expressions are preferred when an expert makes a suitable judgement [ 57 ]. Hence, in the present study, TrFN was employed to calculate the weight of the likelihood and consequence of the risk factors, which were identified from accident data.…”

Section: Methodsmentioning

confidence: 99%

Identifying the Weaker Function Links in the Hazardous Chemicals Road Transportation System in China

Zhang

et al. 2021

IJERPH

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Safety of the hazardous chemicals road transportation system (HCRTS) is an important, complex, social, and environmental sensitive problem. The complexity, dynamics, and multi-link features of HCRTS have made it necessary to think beyond traditional risk analysis methods. Based on the relevant literature, Functional Resonance Analysis Method (FRAM) is a relatively new systemic method for modeling and analyzing complex socio-technical systems. In this study, a methodology that integrates FRAM, fuzzy sets, and risk matrix is presented to quantitatively assess the risks factors representing failure function links in HCRTS. As the strength of function links can be illustrated by the RI (risk index) of risk factors identified in failure function links, 32 risk factors representing 12 failure function links were first identified by accident causes analysis and the framework of FRAM. Fuzzy sets were then utilized to calculate the weight of the likelihood and consequence of the risk factors. Finally, according to the assessment results of the identified risk factors by a two-dimensional risk matrix, the weaker function links in the whole HCRTS chain were identified. HCs road companies, regulatory authorities, relevant practitioners, and other stakeholders should pay more attention to these links.

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A Methodology for Dynamic Assessment of Laboratory Safety by SEM-SD

Cited by 13 publications

References 37 publications

Comprehensive Evaluation of Deep Coal Miners’ Unsafe Behavior Based on HFACS-CM-SEM-SD

Comprehensive Evaluation of Deep Coal Miners’ Unsafe Behavior Based on HFACS-CM-SEM-SD

Dual-Attitude Decision-Making Processes of Construction Worker Safety Behaviors: A Simulation-Based Approach

Identifying the Weaker Function Links in the Hazardous Chemicals Road Transportation System in China

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