Explanation and prediction of accidents using the path analysis approach in industrial units: The effect of safety performance and climate

Human error identification and risk assessment in loading and unloading of petroleum products by road trucks using the SHERPA and fuzzy inference system method

Human error constitutes one of the primary causes of accidents, particularly in the context of loading and unloading operations involving road trucks, especially those carrying petroleum products. The process of identifying and evaluating human errors within these operations involves several key steps. Initially, all sub-tasks associated with loading and unloading are meticulously identified and analyzed utilizing Hierarchical Task Analysis (HTA), achieved through direct observation, document examination, and interviews. Subsequently, potential human error modes within each task are delineated using the Systematic Human Error Reduction and Prediction Approach (SHERPA). Finally, essential data for determining the criticality, probability, and severity of each error are gathered through expert elicitation and the application of Fuzzy Inference Systems (FIS). Through the analysis of SHERPA worksheets, a total of 37 errors during loading operations and 14 errors during unloading operations of petroleum products were identified. Among these errors, the predominant category during loading operations was action errors, comprising 31 instances, while communication errors were the least frequent, occurring only twice. Similarly, action errors were most prevalent during unloading operations, constituting 13 instances. These errors were further categorized and ranked based on their risk levels, resulting in 27 levels for loading operations and 12 levels for unloading operations. The consistent occurrence of action errors underscores the need for implementing control measures to mitigate their frequency and severity. Such strategies may include periodic training sessions to reinforce proper work procedures and the development of monitoring checklists, among other interventions.

The role of organizational factors in promoting workers' health in the construction sector: A comprehensive analysis

INTRODUCTION

The number of physical and mental problems caused by occupational accidents and diseases increases every year. To control them, the safety climate at work is a recognized critical factor. However, a widely applicable model to capture the safety climate for various industries and organizations is lacking.

METHOD

This study proposes a theoretical model to measure the direct and indirect effects of safety climate on workers' physical and mental health, mediated by job satisfaction, in the construction sector. We propose a multidimensional construct of safety climate, considering the most salient factors from the literature, and including psychological capital as a new factor. Using data from the last wave of the European Working Conditions Survey (2015) in Spain, the proposed model was validated using structural equation modeling.

RESULTS

Our findings suggest that to further improve the mental health of construction workers, work-life balance and job rewards and compensation must be prioritized along with safety climate. As for physical health, safety climate and work-life balance are crucial. Finally, we provide some recommendations for construction company managers based on a ranking of all the factors affecting the safety climate and the workers' health.

A fuzzy Bayesian network DEMATEL model for predicting safety behavior

Objectives. Safety behavior significantly affects safety performance in the workplace. This study aimed to develop a Bayesian network (BN) model for managing and improving safety behavior. Methods. This study was carried out in the chemical industries in Iran. The data were gathered by a questionnaire consisting of 13 variables including organization safety priority, systems design, safety communication, safety education, work strategy, human-system interaction, mental workload, environmental distractions, work pressure, fatigue, sleepiness, safety knowledge and locus of control. The BN structure was created using the fuzzy decision-making trial, evaluation laboratory method and expert opinions. Belief updating was used to determine variables with the strongest effect on safety behavior. Results. Locus of control, organization safety priority and safety knowledge were the best predictors of safety behavior. Moreover, it was found that improving organization safety priority and safety knowledge is the best intervention strategy to improve safety behavior significantly. Conclusions. BN is a powerful tool that can model causal relationships among variables. Improving organization safety priority and safety knowledge can lead to the maximum possible level of safety behavior.

Prediction of time in industrial chemical accidents: A survival analysis

BACKGROUND: Chemical accidents have imposed casualties and high economic and social consequences to Iranian industries and society. OBJECTIVE: This study investigated the effect of risk factors involved in occurrences of the chemical accidents and predicted the time of occurrences in Iranian chemical factories. METHODS: A cross-sectional study was implemented in 574 chemical facilities with more than 25 employees from 2018 to 2020. Collecting data instruments were 2 checklists with 15 and 25 three-point Likert scale questions, respectively. Chi square and Monte Carlo tests assessed the relationships between independent risk factors and dependent hazardous chemical accidents. Cox semi-parametric and log-normal parametric models were used to predict the upcoming time of chemical accidents based on the impacts of risk factors understudy. Data analyses were performed using Stata and R software. RESULTS: The results showed that safety data sheets, labeling, fire extinguishing system, safe chemicals storage, separation, loading, transportation and training were statistically significant with occurrences of the chemical accidents (P-value < 0.05). Loading and transportation were mostly related to chemical incidents and reduced significantly the expected time of chemical events (P-value = 0.028). CONCLUSION: Establishing a comprehensive chemical accidents dataset and strict governmental supervision on chemical safety regulations are suggested to decrease the chemical accidents at regional and local levels in chemical plants.

Safety culture system construction in coal mine enterprises from the perspective of hazards: A case study on the Yimei Coal Group

BACKGROUND: The construction of a safety culture in coal mine enterprises is an essential component of coal mine safety management. Current studies do not address the mechanism for forming and constructing systems for coal mine enterprise safety culture, and many studies are based on imperfect theoretical frameworks and unsystematic empirical research, their policy recommendations are not systematic or operable, and they offer no feasible safety culture construction system. OBJECTIVE: This study is devoted to analysing the theoretical basis of safety culture construction in coal mine enterprises from the perspective of hazards and proposing the content, stages and targets of constructing a safety culture and develops pragmatic approaches for coal mining enterprises to improve safety culture. METHODS: A theoretical basis for safety culture construction in coal mine enterprises is proposed from the perspective of hazards by considering accident-causing mechanisms based on hazards. Furthermore, this study applied the case analysis and application to conduct empirical research on the proposed theoretical basis for safety culture construction from the perspective of hazards. RESULTS: Four aspects are proposed to capture the content and objectives of safety culture construction from the perspective of hazards: safety concept, behaviour safety, material state safety, and safety institutions. Furthermore, this paper provides a case study of safety culture construction by the Yimei coal group from the perspective of hazards, identifies the hazards based on the above four aspects, and then identifies preventative measures and controls for the identified hazards. CONCLUSIONS: Constructing a safety culture in coal mine enterprises from the perspective of hazards is operable and practical, and thus this study provides essential theoretical and practical value for improving coal mine safety.

Linking mental health to safety behavior in construction workers: The mediating effect of work ability and sleep quality

BACKGROUND: The severity of occupational accidents and injuries in the construction industry is the greatest across all industries. Few studies have examined the causal relationships among physical and psychological variables affecting the safety behavior of construction workers. OBJECTIVE: This study aimed to investigate the relationships among three factors (metal health, work ability and sleep quality) influencing the safety behavior of construction workers. METHODS: This cross-sectional study was conducted on 204 workers in civil construction projects in Iran. The data were gathered via self-reporting questionnaires. The acquired data were analyzed by the Smart PLS3 software using structural equation modeling with the partial least squares (PLS) regression approach. RESULTS: The R square revealed an acceptable fineness of the structural model. Similarly, as Q square values were higher than 0.15 for all factors, the predictability of the model was approved. The direct effect of mental health on safety behavior was not significant, but work ability and sleep quality had significant direct effects on safety behavior. Moreover, a decrease in mental health significantly reduced construction workers’ sleep quality and work ability. CONCLUSION: The results of this study prove that sleep quality and work ability mediate the relationship between mental health and safety behavior. The deterioration of construction workers’ mental health can increase the risk of unsafe behavior and occupational injuries. Therefore, appropriate measures need to be taken to maintain and improve the mental health of construction workers.

Evaluation and empirical research on the operation effect of the risk precontrol management system of safety in coal mines based on OSWM-TOPSIS

BACKGROUND

Most studies have focused on the establishment and application of the risk precontrol management system for safety in coal mines and have seldom considered the evaluation of the system operation effect.

OBJECTIVE

This study aimed to evaluate the operation effect of risk precontrol management system of safety in coal mines and propose policy suggestions to improve the risk precontrol management level of safety.

METHODS

This study applied the Objective and Subjective Weighting Method (OSWM) combined with the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to conduct evaluation and empirical research on the operation effect of the risk precontrol management system of safety in coal mines.

RESULTS

First, the evaluation index system is mainly composed of six first-level indicators and 30 subordinate secondary indicators. Second, the OSWM combined with TOPSIS is an effective method for operation effect evaluation, which yields accurate and undistorted evaluation results. Third, the calculation reference value of the operation effect in the Gengcun coal mine is 57.34, and its corresponding effect level is level III, which is basically effective. Moreover, the calculation reference values of production equipment management (P4) and inspection, audit and review (P6) are the lowest, while the calculation reference values of risk precontrol management (P1) and auxiliary management (P5) reach the critical value corresponding to effect level I, which indicates a good operation effect.

CONCLUSIONS

Corresponding policy suggestions to improve the risk precontrol management level in the Gengcun coal mine are proposed based on the above evaluation results.