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

• Journal of the Korea Safety Management & Science
• /
• v.6 no.1
• /
• pp.11-23
• /
• 2004

The modem industrial society is developing while growing more diverse and gigantic. Accordingly, occupational injuries or accidents can be caused in various situations, not just in the limited range of workplaces but also in the surroundings, and interest has increased in the prevention of occupational accidents with respect to occupational health and safety, and environment. Thus, this thesis will consider 4MlE (Man, Machine, Method, Material, Environment) as the fundamental causes of accidents and introduce a model of system in which the output of the process control system is replaced by accidents with its input by 4M1E. Furthermore, it will demonstrate how occupational hazardousness can be measured, whereby it can also be rated, by examining the relationship between 4M1E and types of accident in terms of the categories of severity, frequency, and detectability, based on the application of the model to the framework of FMEA.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
• /
• v.21 no.2
• /
• pp.247-253
• /
• 2023

According to NSSC Notice No. 2021-10, safety analysis needs to be introduced in the decommissioning plan. Public and occupational dose analyses should be conducted, specifically for unexpected radiological accidents. Herein, based on the risk matrix and analytic hierarchy process, the method of selecting accident scenarios during the decommissioning of nuclear power plants has been proposed. During decommissioning, the generated spent resin exhibits relatively higher activity than other generated wastes. When accidents occur, the release fraction varies depending on the conditioning method of radioactive waste and type of radioactive nuclides or accidents. Occupational dose analyses for 2 (fire and drop) among 11 accident scenarios have been performed. The radiation doses of the additional exposures caused by the fire and drop accidents are 1.67 and 4.77 mSv, respectively.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2022.06a
• /
• pp.415-416
• /
• 2022

Marine pilot occupational accidents during transfer to/from the ship are at the top of the agenda after several safety campaigns by IMPA and individual attemptsThere is multiple transfer method for the marine pilot, but a most common way is to use the pilot cutter. This paper aims to predict marine pilot occupational accidents before it occurs by using historical data. Since the problem depends on several variables, this paper develops a model by using the random forest method to predict marine pilot accidents before happening with the random forest method by using RStudio software

• Journal of Wellbeing Management and Applied Psychology
• /
• v.7 no.1
• /
• pp.35-41
• /
• 2024

Purpose: This study examines the persistent occurrence of railway accidents despite numerous safety devices, highlighting the multifaceted nature of these incidents. Research design, data and methodology: Utilizing the 4M analysis method, the research investigates a decade's worth of accident reported from the Aviation and Railway Accident Investigation Board to identify risk factors and suggest mitigation measures. Results: The analysis reveals that 57% of railway accidents are attributed to human factors, followed by mechanical (28%), environmental (7%), and management (8%) factors. Conclusions: The study underscores the necessity of prioritizing safety and establishing a unified organizational approach to prevent human error accidents. It calls for an alignment of risk perception between headquarters and field operations, advocating for educational and perceptual changes, as well as systematic improvements to achieve safety goals.

• Safety and Health at Work
• /
• v.7 no.2
• /
• pp.161-165
• /
• 2016

Background: Despite the declining trend of workplace accidents in Republic of Korea, its level is still quite high compared with that in other developed countries. Factors that are responsible for high workplace accidents have not been well documented in Republic of Korea. The main purpose of this paper is to estimate the effects of unions and health and safety committees on workplace accidents in Korean manufacturing firms. We also allow for the interactions between unions and health and safety committees in the analysis. The results obtained in this paper will not only contribute to the literature in this field, but might also be useful for employers and worker representatives who are trying to find an effective way to reduce workplace accidents. Methods: This paper utilizes the 2012 Occupational Safety and Health Trend Survey data, which is a unique data set providing information on workplace injuries and illness as well as other characteristics of participatory firms, representative of the manufacturing industry in Republic of Korea. Results: In estimating the effects of unions and health and safety committees, we build a negative binomial regression model in which the interactions between unions and health and safety committees are permissible in reducing workplace accidents. Conclusion: Health and safety committees were found to reduce the incidence of accidents whereas unionized establishments have higher incidence of accidents than nonunionized establishments. We also found that health and safety committees can more effectively reduce accidents in nonunionized establishments. By contrast, nonexclusive joint committees can more effectively reduce accidents in unionized establishments.

• Safety and Health at Work
• /
• v.10 no.3
• /
• pp.305-313
• /
• 2019

Background: The oil and gas industry is one of the riskiest industries for confined space injuries. This study aimed to understand an overall picture of the causal factors of confined space accidents through analyzing accident reports and the use of a qualitative approach. Methods: Twenty-one fatal occupational accidents were analyzed according to the Human Factors Analysis and Classification System approach. Furthermore, thirty-three semistructured interviews were conducted with employees in different roles to capture their experiences regarding the contributory factors. The content analyses of the interview transcripts were conducted using MAXQDA software. Results: Based on accident reports, the largest proportions of causal factors (77%) were attributed to the organizational and supervisory levels, with the predominant influence of the organizational process. We identified 25 contributory factors in confined space accidents that were causal factors outside of the original Human Factors Analysis and Classification System framework. Therefore, modifications were made to deal with factors outside the organization and newly explored causal factors at the organizational level. External Influences as the fifth level considered contributory factors beyond the organization including Laws, Regulations and Standards, Government Policies, Political Influences, and Economic Status categories. Moreover, Contracting/Contract Management and Emergency Management were two extra categories identified at the organizational level. Conclusions: Preventing confined space accidents requires addressing issues from the organizational to operator level and external influences beyond the organization. The recommended modifications provide a basis for accident investigation and risk analysis, which may be applicable across a broad range of industries and accident types.

• Journal of the Korea Safety Management & Science
• /
• v.25 no.2
• /
• pp.39-48
• /
• 2023

Recently, the crisis of demographic extinction is rising in Korea more than any other country, and it is difficult for industrial sites to maintain without 'foreign workers'. Industrial accidents and accident deaths of foreign workers account for 7.6% and 12.3% of the total, through an in-depth analysis of fatal accidents in the manufacturing industry, differences and similarities between fatal accidents of foreign workers and all fatal accidents were confirmed in terms of occurrence type, workplace size, length of service, employment type, etc. In this study, customized countermeasures were found.

• Journal of the Korea Safety Management & Science
• /
• v.16 no.4
• /
• pp.1-9
• /
• 2014

The occupational health and safety accidents were continuously increased during handling, usage and manufacturing the chemical materials according to increase of small and medium sized enterprises in domestic industries. These accidents mainly resulted from insufficient occupational health and safety management and deteriorative facilities and focused on corresponding operation to minimize the damage of accidents after occurrence. But, it was required that we grasped the occurrence causes of occupational health and safety risk in handling, usage and manufacturing the chemical materials and develop the adequate corresponding operation and system according to the possible occurrence of occupational health and safety risk. This study deals with the development of risk assessment model to derive the risk and important risk of occupational health and safety and then help to construct the self-controlled occupational health and safety system for small and medium sized enterprises handling the chemical materials.

• Journal of the Architectural Institute of Korea Structure & Construction
• /
• v.35 no.11
• /
• pp.155-162
• /
• 2019

The construction industry is the highest safety accident causing industry as 28.55% portion of all industries' accidents in Korea. In particular, falling is the highest accidents type composed of 60.16% among the construction field accidents. Therefore, we analyzed the factors of major disaster affecting the fall accident and then derived feature importances by considering various variables. We used data collected from Korea Occupational Safety & Health Agency (KOSHA) for learning and predicting in the proposed model. We have an effort to predict the degree of occupational fall accidents by using the machine learning model, i.e., Adaboost, short for Adaptive Boosting. Adaboost is a machine learning meta-algorithm which can be used in conjunction with many other types of learning algorithms to improve performance. Decision trees were combined with AdaBoost in this model to predict and classify the degree of occupational fall accidents. HyOperpt was also used to optimize hyperparameters and to combine k-fold cross validation by hierarchy. We extracted and analyzed feature importances and affecting fall disaster by permutation technique. In this study, we verified the degree of fall accidents with predictive accuracy. The machine learning model was also confirmed to be applicable to the safety accident analysis in construction site. In the future, if the safety accident data is accumulated automatically in the network system using IoT(Internet of things) technology in real time in the construction site, it will be possible to analyze the factors and types of accidents according to the site conditions from the real time data.