Analysis of Factors Influencing Miners' Unsafe Behaviors in Intelligent Mines using a Novel Hybrid MCDM Model

A chemical accident cause text mining method based on improved accident triangle

BACKGROUND

With the rapid development of China's chemical industry, although researchers have developed many methods in the field of chemical safety, the situation of chemical safety in China is still not optimistic. How to prevent accidents has always been the focus of scholars' attention.

METHODS

Based on the characteristics of chemical enterprises and the Heinrich accident triangle, this paper developed the organizational-level accident triangle, which divides accidents into group-level, unit-level, and workshop-level accidents. Based on 484 accident records of a large chemical enterprise in China, the Spearman correlation coefficient was used to analyze the rationality of accident classification and the occurrence rules of accidents at different levels. In addition, this paper used TF-IDF and K-means algorithms to extract keywords and perform text clustering analysis for accidents at different levels based on accident classification. The risk factors of each accident cluster were further analyzed, and improvement measures were proposed for the sample enterprises.

RESULTS

The results show that reducing unit-level accidents can prevent group-level accidents. The accidents of the sample enterprises are mainly personal injury accidents, production accidents, environmental pollution accidents, and quality accidents. The leading causes of personal injury accidents are employees' unsafe behaviors, such as poor safety awareness, non-standard operation, illegal operation, untimely communication, etc. The leading causes of production accidents, environmental pollution accidents, and quality accidents include the unsafe state of materials, such as equipment damage, pipeline leakage, short-circuiting, excessive fluctuation of process parameters, etc. CONCLUSION: Compared with the traditional accident classification method, the accident triangle proposed in this paper based on the organizational level dramatically reduces the differences between accidents, helps enterprises quickly identify risk factors, and prevents accidents. This method can effectively prevent accidents and provide helpful guidance for the safety management of chemical enterprises.

Game analysis of enterprise safety investment and employee safety behavior strategy evolution in high-risk industries

This paper aims to explore the influential relationship between the decision-making of investment of enterprise safety and employee safety behavior strategy selection, thus improve the effectiveness of decision-making. Based on traditional game theory, this paper establishes an evolutionary game model of enterprise safety investment and employee safety behavior strategy selection, and conducts numerical simulation analysis. The result shows:when the security investment cost is greater than the security investment benefit, the employee's security behavior strategy choice is significant for the enterprise security investment strategy decision; when the security investment benefit is greater than the security investment cost, the enterprise security investment decision is not affected by the employee safety behavior strategy; the choice of employee safety behavior strategy is not affected by the choice of enterprise safety investment strategy. The conclusion can provide a reference basis for enterprise safety production decision-making, which has certain theoretical and practical significance.

Investigation of the Suppression of Methane Explosions by N2/CO2 Mixtures in Different Proportions

To characterize the inerting effect of N₂/CO₂ mixtures containing various proportions on methane-air explosions, a series of experiments were conducted in a 20 L spherical vessel under the normal temperature (25 °C) and normal pressure (101 kPa). Six concentrations (10, 12, 14, 16, 18, and 20%) of N₂/CO₂ mixtures were selected to analyze the suppression of methane explosion by N₂/CO₂ mixtures. The results indicated that the maximum explosion pressure (p _max) of methane explosions was 0.501 MPa (17% N₂ + 3% CO₂), 0.487 MPa (14% N₂ + 6% CO₂), 0.477 MPa (10% N₂ + 10% CO₂), 0.461 MPa (6% N₂ + 14% CO₂), and 0.442 MPa (3% N₂ + 17% CO₂) in the presence of the same N₂/CO₂ concentration, and similar decreases in the rate of pressure rise, flame propagation velocity, and production of free radicals were observed. Therefore, with the increase of CO₂ concentration in the gas mixture, the inerting effect of N₂/CO₂ was enhanced. Meanwhile, the whole process of the methane combustion reaction was affected by N₂/CO₂ inerting, which was mainly attributed to heat absorption and dilution of the N₂/CO₂ mixture. N₂/CO₂ with a greater inerting effect leads to lower production of free radicals under the same explosion energy and a lower combustion reaction rate at the same flame propagation velocity. The findings of the current research provide references for the design of safe and reliable industrial processes and the mitigation of methane explosions.

Research on Resilience Evaluation of Coal Industrial Chain and Supply Chain Based on Interval Type-2F-PT-TOPSIS

As unexpected events such as natural disasters, the COVID-19 pandemic, and overseas containment have caused inevitable shocks to the energy industrial chain and supply chain, the current global energy crisis is intensifying, and different countries and regions have adopted different strategies according to the characteristics of their own national resource endowments in order to cope with energy security. Maintaining the security of the coal industrial chain and supply chain is a prerequisite for energy security to be effectively ensured, considering the main position of coal in China’s energy. Therefore, in the face of multiple uncertain risk factors under today’s momentous changes, this paper constructs an industrial coal chain and supply chain resilience evaluation indicator system from the perspective of resilience, based on four representational capabilities of resilience, namely preparedness, absorptive capacity, recovery capacity, and adaptability, in order to profoundly understand and enhance the resilience of the coal industrial chain and supply chain. An integrated method combining Interval Type-2 Fuzzy Prospect Theory and Technique for Order Preference by Similarity to an Ideal Solution (Interval Type-2F-PT-TOPSIS) is proposed for evaluating the resilience level of the coal industrial chain and supply chain. In the case of Shaanxi Province in China, it was found that the worst level of resilience of the coal industrial chain and supply chain in Shaanxi Province was in 2018, and the best was in 2021. Finally, based on the evaluation results, recommendations are provided to the key nodes of the industrial chain and supply chain in Shaanxi Province with a view to improving their resilience levels to cope with uncertain risks.

Analysis of Risk Factors of Coal Chemical Enterprises Based on Text Mining

Coal chemical enterprises have many risk factors, and the causes of accidents are complex. The traditional risk assessment methods rely on expert experience and previous literature to determine the causes of accidents, which has the problems such as lack of objectivity and low interpretation ability. Analyzing the accident report helps to identify typical accident risk factors and determines the accident evolution rule. However, experts usually judge this work manually, which is subjective and time-consuming. This paper developed an improved approach to identify safety risk factors from a volume of coal chemical accident reports using text mining (TM) technology. Firstly, the accident report was preprocessed, and the Term Frequency Inverse Document Frequency (TF-IDF) was used for feature extraction. Then, the K-means algorithm and apriori algorithm were developed to cluster and for the association rule analysis of the vectorized documents in the TF-IDF matrix, respectively to quickly identify the hidden risk factors and the relationship between risk factors in the accident report and to propose targeted safety management measures. Using the sample data of 505 accidents in a large coal chemical enterprise in Western China in the past seven years, the enterprise accident reports were analyzed by text clustering analysis and association rule analysis methods. Through the analysis, six accident clusters and 13 association rules were obtained, and the main risk factors of each accident cluster were further mined, and the corresponding management suggestions were put forward for the enterprise. This method provides a new idea for coal chemical enterprises to make safety management decisions and helps to prevent safety accidents.

Research on the formation mechanism of information cocoon and individual differences among researchers based on information ecology theory

Introduction

Choosing to only retrieve and read academic information related to their own research field is conducive to researchers' in-depth understanding of their own research issues, and also reduces the pressure of researchers' information retrieval, but may bring about the effect of information cocoon.

Methods

Based on the information ecology theory, a theoretical model is built from the aspects of information people, information, information environment and information technology, and relevant data is collected through questionnaires to verify assumptions. To explore the formation path of information cocoon for scientific researchers and the differences between different types of scientific researchers.

Results

Different gender, education background, identity, age and team size of scientific researchers will lead to different dimensions in the process of producing information cocoon; Community influence, information homogeneity and value identification are important factors influencing the formation of information cocoon room for scientific researchers; Community influence and information homogeneity positively affect value identification.

Discussion

In the future research work, researchers should pay attention to the influence of information homogeneity, community influence and value identification.

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

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.

An Investigation of Employees' Intention to Comply with Information Security System-A Mixed Approach Based on Regression Analysis and fsQCA

Employee security compliance behavior has become an important safeguard to protect the security of corporate information assets. Focusing on human factors, this paper discusses how to regulate and guide employees' compliance with information security systems through effective methods. Based on protection motivation theory (PMT), a model of employees' intention to comply with the information security system was constructed. A questionnaire survey was adopted to obtain 224 valid data points, and SPSS 26.0 was applied to verify the hypotheses underlying the research model. Then, based on the results of a regression analysis, fuzzy set qualitative comparative analysis (fsQCA) was used to explore the conditional configurations that affect employees' intention to comply with the information security system from a holistic perspective. The empirical results demonstrated that perceived severity, perceived vulnerability, response efficacy, and self-efficacy all positively influenced the employees' intention to comply with the information security system; while rewards and response costs had a negative effect. Threat appraisal had a greater effect on employees' intention to comply with the information security system compared to response appraisal. The fsQCA results showed that individual antecedent conditions are not necessary to influence employees' intention to comply with an information security system. Seven pathways exist that influence an employees' intention to comply with an information security system, with reward, self-efficacy, and response cost being the core conditions having the highest probability of occurring in each configuration of pathways, and with perceived severity and self-efficacy appearing in the core conditions of configurations with an original coverage greater than 40%. Theoretically, this study discusses the influence of the elements of PMT on employees' intention to comply with an information security system, reveals the mechanism of influence of the combination of the influencing factors on the outcome variables, and identifies the core factors and auxiliary factors in the condition configurations, providing a new broader perspective for the study of information security compliance behavior and providing some theoretical support for strengthening enterprise security management. Practically, targeted suggestions are proposed based on the research results, to increase the intention of enterprise employees to comply with information security systems, thereby improving the effectiveness of enterprise information security management and the degree of information security in enterprises.

Study on the Grayscale Characteristics of Borehole Images of Progressive Failure of Coal Bodies with Different Moisture Contents

The failure process of a coal body around a borehole has progressive characteristics. Image characteristics can visually characterize the stress and failure characteristics of the coal body around a borehole during progressive failure. To investigate the effect of the moisture content on the progressive failure of the coal body around the borehole, an image test system for the deformation and fracture of coal rock was used, and progressive failure tests of coal body specimens with different moisture content conditions around boreholes were performed. We acquired images of the deformation field during the entire process of specimen failure. Based on the grayscale image theory, the variation in the grayscale characteristic parameters of the progressive failure process was analyzed. The results show that throughout the progressive failure of coal bodies with different moisture contents around a borehole, the main specimen failure can be divided into six stages: compression density, elastic deformation, crack initiation and stable extension, crack nonstable extension, post-peak softening, and post-peak failure. With increasing moisture content, the σcd/σf values of the 20%- and 40%-moisture-content specimens were 5.1% and 11.3% lower than those of the dry specimens, respectively, and the maximum uniaxial compressive strength σf was 5.1% and 17.4% lower than those of the dry specimens, respectively. The number of cracks that developed decreased. The grayscale histogram had a reduced grayscale peak at each stage, and the surface distortion diminished. The declining grayscale mean curve indicates a lagging development of stress concentration zones. The declining grayscale entropy curve indicates that macroscopic cracks form. The rising grayscale standard deviation curve indicates the delayed development of strain localization zones and weakening of specimen damage. The study explains the deformation and failure characteristics of the coal body around the borehole and the variation in grayness.

How Does Public Sentiment Affect the Socially Responsible Behavior of Construction Enterprises?

The negative environmental impact of the construction sector has garnered global attention, and as the “primary force” in achieving the “double carbon” target, green development is urgent, and social responsibility practices cannot be postponed. An evolutionary game model was constructed by combining the rank-dependent expected utility (RDEU) theory and the evolutionary game theory to understand the interaction mechanism between participants’ emotions and decisions, taking into account the characteristics of construction enterprises and the public regarding irrational decisions under heterogeneous emotional combinations. The study demonstrates that: (1) there is probability in the choice of rational strategies, and emotion is an irrational factor that can affect strategy choice. (2) The evolutionary trend of the strategy choice of the game subjects is altered by emotional intensity and emotional propensity. The optimism of construction enterprises inhibits their socially responsible practice, and the pessimism of the public promotes the probability of their negative strategy choice. Furthermore, moderate optimism is a safety valve for the public’s positive strategy choice. (3) The interaction of emotional states leads to a heterogeneity of strategy choices exhibited under different combinations of emotions, with the emotions of construction companies having a more dominant influence on strategy. Finally, we make some feasible recommendations for improving social responsibility practices and preventing mass incidents by boosting emotional monitoring and guidance for construction businesses and the general public. Overall, this study provides important information about how to be socially responsible, maintain good relationships with the public, and protect the environment.

Integrated Approach for Safety Culture Factor Evaluation from a Sustainability Perspective

Traditionally, sustainable development has been seen as a combination of three pillars: economic, social and environmental development. In recent years, another one has been added to these three pillars, namely culture, as being indispensable in achieving sustainable development. This study proposes an integrated approach for the identification and classification of safety culture factors in the company in a sustainability context. The research design was based on the assumption that safety culture is part of organizational culture that should support the development of corporate sustainability. Firstly, the identification of the safety culture factors (SCFs) based on the literature review was presented. Then, the ISM method was used to identify the interaction between SCFs and to develop the hierarchical structure of these factors. In the next step, ISM was integrated with the MICMAC method to cluster the factors based on driving power and dependence power into four categories. Finally, safety culture factors with high driving power were rated using the fuzzy TOPSIS method from the sustainability dimension perspective. This approach was used in an automotive industry company to improve and develop the company's practices aimed at implementing a sustainable development strategy. A sensitivity analysis was also carried out to monitor the robustness of the approach.

The Double-Edged Sword of Safety Training for Safety Behavior: The Critical Role of Psychological Factors during COVID-19

Safety training (ST) is the primary means of avoiding unsafe behaviors, but it has not achieved the expected impact on improving workplace safety because of the high psychological stress it brings to workers. The coronavirus disease 2019 (COVID-19) further threatens workers' psychological conditions, thereby diminishing the effectiveness of ST. However, the existing literature has mainly laid emphasis on the bright side of ST and neglected examining its impact on safety behavior (SB) from detrimental psychological factors. Drawing from the conservation of resources theory, a novel two-staged model was established to understand how these psychological factors mediate and moderate the association between ST and SB. We incorporated resource consumption (e.g., role overload (RO) and COVID-19-related task setbacks) and resource generation (e.g., psychological resilience) into the model to consider both detrimental and protective psychological factors against ST. We then implemented a time-separated, three-wave data collection on a sample of frontline workers to validate this hypothetical model. Consistent with our hypothesis, RO played a significant mediating role between ST and SB, that is, ST leads to RO, and in turn, holds up SB. Surprisingly, contrary to our hypothesis, COVID-19-related task setbacks weakened the negative and indirect impact of ST on SB via RO. This is one of the first empirical studies to highlight how detrimental psychological factors caused by ST constrict or amplify SB. In practice, the efficacy of ST can be enhanced by cultivating psychological resilience and clarifying employees' job responsibilities to reduce the ambiguity of roles.

Safety evaluation of rail transit vehicle system based on improved AHP-GA

The rail transit vehicle system is an important subsystem with the most frequent operation accidents and the most direct impact on passengers. Based on the particularity of the vehicle system and the complexity of the system, the hierarchical analysis method (AHP) is used to evaluate its safety. High-order judgment matrix often has inconsistency, and the judgment matrix consistency guarantee is the key to the hierarchical analysis method applied. Based on the hierarchical analysis principle, this paper corrects the inconsistency judgment matrix and realizes the optimization calculation based on the genetic algorithm. This paper constructs a vehicle system safety evaluation index system including 26 indexes at three layers and uses the fuzzy comprehensive evaluation method to evaluate the system safety level. The results show that the calculation results based on the improved AHP-GA are significantly better than that based on the conventional AHP method. The comprehensive evaluation conclusion of the case is "average", and the safety level of the vehicle system of the case enterprise needs to be strengthened.

Game Analysis of the Evolution of Energy Structure Transition Considering Low-Carbon Sentiment of the Decision-Makers in the Context of Carbon Neutrality

Countries have started to aggressively undertake energy structure transformation strategies in order to reach the objective of carbon neutrality. Both clean and efficient coal energy use and clean energy use will be crucial to the process of changing the energy structure since the two cannot be totally replaced within a short period of time. In this study, we quantify emotions as an irrational factor, combine them with an evolutionary game using RDEU theory, and build an evolutionary game model between government regulators and energy consumers. We then analyze how low-carbon emotions of decision-makers affect their choice of strategy and the transformation of the energy structure. The findings support that by affecting the relative importance of each strategic choice, emotions have a profound impact on the evolutionary steady state of the system. Appropriate stress and anxiety can increase decision-makers’ feelings of responsibility, while pleasant emotions frequently support strategic conduct. The main countermeasures are as follows: Allow government regulators and energy consumers to properly release positive information, with government regulators forming subsidies and energy consumers actively cooperating and promoting low-carbon activities. This will properly guide the low-carbon sentiment of game subjects to keep them realistically pessimistic.

Evolutionary Game Analysis of Shared Manufacturing Quality Synergy under Dynamic Reward and Punishment Mechanism

Quality improvement is crucial for manufacturing, and existing research has paid less attention to the influence of regulatory factors and irrational factors of decision makers. Considering the impact of the reward and punishment strategy of the shared platform on quality decision-making, this paper introduces prospect theory and mental account theory into the process of multi-agent evolutionary game of shared manufacturing, constructs a co-evolutionary game model of shared manufacturing quality synergistic improvement under the dynamic reward and punishment mechanism, and analyzes the dynamic evolution law of each game agent. The research results show that: (1) The synergistic improvement of shared manufacturing quality is the consequence of the combined action of numerous interrelated and interacting factors, rather than the linear effect of a single element. (2) Although the combination of multiple incentive and punishment methods can significantly alter the effect of shared manufacturing quality synergy, there are certain effectiveness gaps. (3) The subsidy mechanism can effectively compensate for the effectiveness gap of the reward and punishment mechanism, and it can also strengthen the internal driving force of shared manufacturing quality coordination. The main management insights are as follows: (1) Consider strong external regulation to be the framework constraint, and positive internal control to be the detail specification. (2) Create a reliable reward and punishment mechanism and dynamically alter the intensity of rewards and penalties. (3) To close the effectiveness gap, strengthen the subsidy mechanism as an essential addition to the incentive and punishment mechanisms. This study can give a new reference path for quality improvement of shared manufacturing, allowing shared manufacturing to play a more constructive role in supporting the transformation and development of the manufacturing industry.