• International Journal of Safety
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• 제7권2호
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• pp.23-26
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• 2008

This study focuses on the issue of control performance of safety budget for preventing and reducing industrial accidents in Korea. The effect of safety budget such as industrial accident prevention fund on the safety performance is statistically examined first. The role and control performance of industrial accident prevention fund is particularly addressed to reduce the related accidents. The effectiveness of the industrial accident prevention fund-industrial accident relationship is then explained with a simple PI control mechanism.

• 대한안전경영과학회지
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• 제10권3호
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• pp.29-33
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• 2008

According to statistics released by the Ministry of Labor for the past 6 years, work-related accidents in the construction industry have been on the continued increase, resulting in social and economic losses that are difficult to determine at an exact amount. However, the number will likely get much bigger if unreported cases are included, considering the fact that the aforementioned statistics are based soley on the applications filed with Korea Workers' Compensation and Welfare Service. The practice of businesses choosing not to report and dealing with industrial accidents in an unauthorized manner is defined as "concealment of industrial accident". The reason the employers tend to engage in the concealment practice even at their huge cost is a "pre-qualification" scheme for the applicants in the government procurement process. Under the pre-qualification scheme, the applicants with a high rate of industrial accidents receive a low grade and become less attractive candidates in the procurement process, thus losing an opportunity to win a contract. Such failure relates directly to the fate of business organizations, to survive or not. That is why they are making all-out efforts to obtain a high grade in the pre-qualification evaluation. With regard to the accident-concealment problem, the following can be mentioned as preventive measures: (1) To exclude a rate of industrial accidents from the pre-qualification scheme; (2) To strengthen the institution of imposing penalties on the occurrence of industrial accidents; (3) To introduce private insurance system to the current industrial accident compensation insurance; and (4) To give non-recognition treatment to industrial accidents that were not reported upon occurrence. In conclusion, the concealment problem can be resolved if the aforementioned measures are to be taken continuously along with corrective measures against institutional deficiencies.

• Safety and Health at Work
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• 제11권3호
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• pp.266-274
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• 2020

Background: From only frequency rate of industrial accidents, it is difficult to define the industry composition of accident statistics in a nation. This study aims to propose and develop a new index for measuring the degree of concentration of industrial accidents using the concept of the Herfindahl-Hirschman Index in the case of European countries. Methods: Using the concept of the Herfindahl-Hirschman Index, the concentration index of accidents in the country is developed, and the conditions of European countries are compared using indexes of frequency rate and concentration ratio. Results: The frequency rate and concentration ratio of fatal and nonfatal accidents in European countries are compared. According to the economic condition and geographical position, different patterns of accidents concentration are presented in terms of frequency rate and concentration ratio. Conclusion: We develop the concentration index of industrial and occupational accidents that identifies the industrial ratio of accident occurrence, and the differentiated strategy can be formulated such as approaches to reducing frequency and prioritizing target industries.

• 한국안전학회지
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• 제29권6호
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• pp.1-8
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• 2014

Safety certification and inspection of dangerous machines and equipments used in industries are to save lives of workers and properties involved. Cause analysis of industrial accidents is essential to prove the effectiveness of such certification and inspection. This study focuses on suggesting systematic method for cause analysis of industrial accidents associated with dangerous machines and devices. Incorporating transition from the current user-oriented indirect regulations to more manufacturer and user balanced direct regulations, suggested method coupled with safety certification, safety inspection, safety management and safety education will guarantee more effective prevention of industrial accidents.

• 대한안전경영과학회지
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• 제25권2호
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• pp.39-48
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• 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.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2021년도 가을 학술논문 발표대회
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• pp.94-95
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• 2021

With the recent advancement of the construction industry, interest in it is growing as the accident rate in the construction industry continues to increase due to the enlargement and complexity of the construction scale. These social issues are focused on the safety of construction work, and research on construction industrial accidents is continuously being conducted, but research on measures to reduce construction industrial accidents is surprisingly insufficient. Therefore, in this study, research on reduction measures to increase the safety of construction industrial accidents conducted for 5 years from 2017 to 2021 is investigated and compared, and it is intended to be used as basic data for future construction industrial accident reduction measures.

• 한국안전학회지
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• 제20권4호
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• pp.130-137
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• 2005

Decision tree algorithm is one of the data mining techniques, which conducts grouping or prediction into several sub-groups from interested groups. This technique can analyze a feature of type on groups and can be used to detect differences in the type of industrial accidents. This paper uses C4.5 algorithm for the feature analysis. The data set consists of 24,887 features through data selection from total data of 25,159 taken from 2 year observation of industrial accidents in Korea For the purpose of this paper, one target value and eight independent variables are detailed by type of industrial accidents. There are 222 total tree nodes and 151 leaf nodes after grouping. This paper Provides an acceptable level of accuracy(%) and error rate(%) in order to measure tree accuracy about created trees. The objective of this paper is to analyze the efficiency of the C4.5 algorithm to classify types of industrial accidents data and thereby identify potential weak points in disaster risk grouping.

• 대한안전경영과학회지
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• 제8권1호
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• pp.53-64
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• 2006

Many researches and analyses have been focused on industrial accidents in order to predict and reduce them. As a similar endeavor, this paper is to develop an expert system for prevention of industrial accidents. Although various previous studies have been performed to prevent industrial accidents, these studies only provide managerial and educational policies using frequency analysis and comparative analysis based on data from past industrial accidents. As an initial step for the purpose of this study, this paper provides a comparative analysis of 4 kinds of algorithms including CHAID, CART, C4.5, and QUEST. Decision tree algorithm is utilized to predict results using objective and quantified data as a typical technique of data mining. Enterprise Miner of SAS and Answer Tree of SPSS will be used to evaluate the validity of the results of the four algorithms. The sample for this work was chosen from 10,536 data related to manufacturing industries during three years$(2002\sim2004)$ in korea. The initial sample includes a range of different businesses including the construction and manufacturing industries, which are typically vulnerable to industrial accidents.

• 대한안전경영과학회지
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• 제25권3호
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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.

• 한국안전학회지
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• 제13권4호
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• pp.279-285
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• 1998

This study investigated human error characteristics of the 42 fatal industrial accidents reported by staff members of Korea Industrial Safety Corporation. Various types of human error were judged to be primary contributing factors in about 74 percent of the cases. Most of human error made by involved industrial operators resulted from two types of mistakes: (1) mistake in judgement of work situation, and (2) omission in daily check. It was concluded that preparation/observance for work procedure manuals, danger predication training and enforcement/Education of daily check routine would be effective preventive tools for these types of human error attributable to fatal industrial accidents.