• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.30 no.1
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• pp.39-49
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• 2020

Objectives: We investigated the status of accidents and deaths caused by chemical leakage and skin contact in Korea. The purpose of this study was to produce and provide technical reference data for the efficient management of accidents and the rational management of accidental chemicals. Methods: Accidents and deaths caused by chemical leakage and skin contact in industry were investigated. Based on 68 accident reports related to chemical leakage and skin contact, the causes of accidental deaths were analyzed. In addition, we investigated the chemical substances and articles that caused these accidents and deaths. Based on the results of the investigation, the causes of accidents caused by chemical leakage and skin contact were identified and practical management measures for the chemicals were suggested. Results and Conclusions: In 2018, 372 people suffered from chemical leaks and skin contact, up by 123 (about 49.4%) from the previous year. The number of accident deaths was 14, an increase of five (about 55.6%) from the previous year. In the last three years (2016-2018), 91 chemical substances and article groups were involved in accidents caused by chemical leakage and skin contact. There were 16 chemical substance and article groups involved in accidental deaths. There were ten cases of accidents involving two or more casualties due to chemical leakage and skin contact, and 23 deaths occurred. Most of these accidental deaths were caused by subcontractor workers outsourcing risks. Therefore, there is an apparent need to strengthen the responsibility for safety and health among subcontractors.

• Journal of the Korea Safety Management & Science
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• v.25 no.3
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• pp.63-71
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• 2023

The construction industry stands out for its higher incidence of accidents in comparison to other sectors. A causal analysis of the accidents is necessary for effective prevention. In this study, we propose a data-driven causal analysis to find significant factors of fatal construction accidents. We collected 14,318 cases of structured and text data of construction accidents from the Construction Safety Management Integrated Information (CSI). For the variables in the collected dataset, we first analyze their patterns and correlations with fatal construction accidents by statistical analysis. In addition, machine learning algorithms are employed to develop a classification model for fatal accidents. The integration of SHAP (SHapley Additive exPlanations) allows for the identification of root causes driving fatal incidents. As a result, the outcome reveals the significant factors and keywords wielding notable influence over fatal accidents within construction contexts.

• Safety and Health at Work
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• v.8 no.1
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• pp.59-66
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• 2017

Background: Despite considerable efforts made in recent years, the industrial accident rate and the fatality rate in the Republic of Korea are much higher than those in most developed countries in Europe and North America. Industrial safety policies and safety regulations are also known to be ineffective and inefficient in some cases. Methods: This study focuses on the quantitative evaluation of the effectiveness of direct safety regulations such as safety certification, self-declaration of conformity, and safety inspection of industrial machines in the Republic of Korea. Implications on safety policies to restructure the industrial safety system associated with industrial machines are also explored. Results: Analysis of causes in industrial accidents associated with industrial machines confirms that technical causes need to be resolved to reduce both the frequency and the severity of such industrial accidents. Statistical analysis also confirms that the indirect effects of safety device regulation on users are limited for a variety of reasons. Safety device regulation needs to be shifted to complement safety certification and self-declaration of conformity for more balanced direct regulations on manufacturers and users. An example of cost-benefit analysis on conveyor justifies such a transition. Conclusion: Industrial safety policies and regulations associated with industrial machines must be directed towards eliminating the sources of danger at the stage of danger creation, thereby securing the safe industrial machines. Safety inspection further secures the safety of workers at the stage of danger use. The overall balance between such safety regulations is achieved by proper distribution of industrial machines subject to such regulations and the intensity of each regulation. Rearrangement of industrial machines subject to safety certification and self-declaration of conformity to include more movable industrial machines and other industrial machines with a high level of danger is also suggested.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.1-7
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• 2017

Forensic Engineering is the art and science of professionals qualified to serve as engineering experts in courts of law or in arbitration proceedings. Buses using compressed natural gas (CNG) trend to be extended in use internationally as optimal counterplan for reducing discharge gas of light oil due to high concern about environment. However, CNG buses is equipped with composite pressure vessels (CPVs); since the CPVs contain compressed natural gas, the risks in the case of accident is very high. In this study, the bursting test for the pressure vessel depending on the heat treatment conditions of the vessel in which the actual ruptured accident occurred, after the bursting test, the fracture pattern analysis had performed. The mechanical materials properties test using Instrumented Indentation Test had performed to confirm the mechanical properties for each heat treatment cases. Also, the fractography analysis and metallographic analysis had performed to find out the difference of each heat treatment case. By comparing normal vessel with abnormal vessel which have defect of heat treatment conditions in term of the bursting patterns and characteristics of containers using various forensic engineering methods, especially, it is possible to understand how important the heat treatment process is in the high pressure vessel unlike any product.

• Nuclear Engineering and Technology
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• v.50 no.2
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• pp.280-291
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• 2018

In the framework of OECD/NEA Working Group on Fuel Safety, a RIA fuel-rod-code Benchmark Phase I was organized in 2010-2013. It consisted of four experiments on highly irradiated fuel rodlets tested under different experimental conditions. This benchmark revealed the need to better understand the basic models incorporated in each code for realistic simulation of the complicated integral RIA tests with high burnup fuel rods. A second phase of the benchmark (Phase II) was thus launched early in 2014, which has been organized in two complementary activities: (1) comparison of the results of different simulations on simplified cases in order to provide additional bases for understanding the differences in modelling of the concerned phenomena; (2) assessment of the uncertainty of the results. The present paper provides a summary and conclusions of the second activity of the Benchmark Phase II, which is based on the input uncertainty propagation methodology. The main conclusion is that uncertainties cannot fully explain the difference between the code predictions. Finally, based on the RIA benchmark Phase-I and Phase-II conclusions, some recommendations are made.

• Journal of the Korean Society of Safety
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• v.38 no.4
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• pp.23-31
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• 2023

Revising the Occupational Safety and Health Act led to enacting and revising related laws and systems, such as placing fire observers in hot workplaces. However, the operating standards in such cases are still ambiguous. Although fire accidents occur through multiple and multi-step factors, the hazards of fire accidents have been identified in this study as individual rather than interrelated factors. The aim has been to identify multiple factors of accidents, outlining fire and explosion accidents that recently occurred in the domestic manufacturing industry. First, major keywords were extracted through text mining. Then representative accident types were derived by combining the main keywords through the co-word network analysis to identify the hazards and their relationships. The representative fire accidents were identified as six types, and their major hazards were then addressed for improving safety measures using the identification of hazards in the "Risk Assessment" tool. It is found that various safety measures, such as professional fire observers' training and clear placement standards, are needed. This study will provide useful basic data for revising practical laws and guidelines for fire accident prevention, system supplementation, safety policy establishment, and future related research.

• Korean Journal of Construction Engineering and Management
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• v.21 no.3
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• pp.28-38
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• 2020

The large-scaled and high-rise construction structures in recent years have increased high place work, leading to an increase in falling accidents (hereinafter, "accidents"). The need for prediction and management of unsafe acts of workers at construction sites has been raised as unsafe acts of workers are identified as the main cause of industrial accidents. This research aims at deriving the improvement effect of unsafe acts by presenting the relationship between unsafe acts of workers and accidents at construction sites as a probability. Unsafe acts of workers were derived based on the analysis of accident cases. In addition, surveys were conducted to calculate the probability of occurrence of accidents caused by unsafe acts (hereinafter, 'accident probability'). The Event Tree Analysis (ETA) was utilized to confirm the final probability according to the combination of unsafe acts and improvement effect. The accident probability by unsafe act was found to be the highest for working after drinking (95.41%) and to be the lowest for equipment and machine utilization (65.70%). The accident probability according to a combination of unsafe acts was the highest when all of the unsafe acts were conducted (13.23%) and was the lowest when none of the unsafe acts were conducted (0.00%).

• Journal of the Korea Safety Management & Science
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• v.11 no.1
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• pp.1-6
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• 2009

The specific feature of trains as a means of transportation is that, on one side, at once they can carry big loads but, at the same time, if an accident occurs, it potentially leads to many human casualties or big material losses. Especially, train accidents caused by bad weather conditions result in many fatal losses of human lives and property. In Korea many railways run either in mountainous areas or along rivers thus making them especially susceptible to natural hazards. The types of damages inflicted by heavy rains resulting from rapidly changing meteorological conditions are diverse; and not only their scope is big but also they repeat regularly. Consequently, this study analyses the reasons why such effects of heavy rains on the railway conditions, damage to the railways caused by heavy rains or cases of stone fall as well as other types of accidents are not avoided. Study also, on the basis of laws related to movement in poor weather conditions and specifics of train braking, identifies systematic and technical problems and suggests and emphasizes new complex measures on their prevention.

• Journal of the Korean Society of Safety
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• v.36 no.5
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• pp.52-60
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• 2021

As the prevention of fatal accidents is considered an essential part of social responsibilities, both government and individual have devoted efforts to mitigate the unsafe conditions and behaviors that facilitate accidents. Several studies have analyzed the factors that cause fatal accidents and compared them to those of non-fatal accidents. However, studies on mathematical and systematic analysis techniques for identifying the features of fatal accidents are rare. Recently, various industrial fields have employed machine learning algorithms. This study aimed to apply machine learning algorithms for the classification of fatal and non-fatal accidents based on the features of each accident. These features were obtained by text mining literature on accidents. The classification was performed using four machine learning algorithms, which are widely used in industrial fields, including logistic regression, decision tree, neural network, and support vector machine algorithms. The results revealed that the machine learning algorithms exhibited a high accuracy for the classification of accidents into the two categories. In addition, the importance of comparing similar cases between fatal and non-fatal accidents was discussed. This study presented a method for classifying accidents using machine learning algorithms based on the reports on previous studies on accidents.

• Journal of the Korean Society of Safety
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• v.34 no.3
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• pp.83-88
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• 2019

The 7,993 cases of Survey Report of Fatal Industrial Accidents conducted jointly by the MEOL and the KOSHA for the recent seven years(2007-2013) were categorized according to personal and occupational characteristics, industry types, business sizes, job types, activities at the time accident, types of accidents, material agents(assailing materials), unsafe conditions, and unsafe acts. And it is found that among the 72.2 percent of fatal occupational accidents in the construction and manufacturing industries are caused by falling, sticking, bumping and being caught under objects & overturning. For this study, through the empirical analysis on causes of fatal industrial accidents, was used to identity high risk groups based on total data of 7,993 victims of occupational accidents. An annual fatal occupational injury (FOI) rate per 10,000 workers was about 0.47‱. The middle-aged group and the elderly group showed the highest FOI rates per 10,000 workers (0.73‱, 0.80‱), and the daily workers showed the highest FOI rate (1.46‱), and the craft and related trades workers showed the highest FOI rate (2.17‱). In case of industry type the mining industry (7.26‱) showed the highest FOI rate, followed by the sewerage, waste management, materials recovery and remediation activity industry (3.91‱) and the construction industry (2.71‱). The primary high risk target group that requires a strategy designed to reduce fatal occupation injuries caused by falling and bumping & contact(collision) is the construction industry, and the secondary high risk target group in the construction industry is classified as the equipment, machine operating and assembling workers in the construction industry, those aged 50 years old and above need the prevention measures against bumping & contact(collision) and being caught under an object & falling(objects), while those aged less than 50 years old need prevention measures against falling(persons).