• Safety and Health at Work
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• v.11 no.3
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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.

• Journal of the Korean Society of Safety
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• v.34 no.2
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• pp.1-6
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• 2019

This study focuses on the evaluation of severity measures used for accidents associated with industrial machines and devices. In particular, duration of medical treatment, duration of work loss, number of deaths in an individual accident associated with industrial machines and devices are evaluated in various ways to assess the severity of the accident. The number of accidents with work loss of longer than 1 year as the severity measure and the number of accidents as the frequency measure appeared to be the most discriminating information and allow risk assessment based on these frequency and severity measures for grouping of industrial machines and devices. Results of such risk assessment further confirmed the re-classification of industrial machines and devices that are currently subject to safety certification (SC) and self-declaration of conformity (SDC) or selection of those machines and devices that are newly subject to SC and SDC.

• Journal of the Korean Society of Safety
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• v.31 no.1
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• pp.1-6
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• 2016

Severity and frequency of industrial accidents are typically used to assess the "absolute" risk associated with the industrial machines and devices ("items") which are subject to safety certification or self-declaration of conformity. However, the "relative" risk associated with a particular item can further be assessed based on unit severity and unit frequency where the total number of item in use is taken into account. This study first attempts to estimate the total number of each item in use which was recently selected for safety certification or self-declaration of conformity. The appropriateness of such selection is recapitulated based on the relative risk involved. Analysis results indicate that depending on items, the relative risk is differentiated from the absolute risk. Recent selection of items for safety certification or self-declaration of conformity is then revisited for its validity. The relative risk based on unit severity and unit frequency of industrial accidents, together with the absolute risk, may be used to further categorize items for safety certification or self-declaration of conformity in the future.

• Journal of the Korean Society of Safety
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• v.33 no.5
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• pp.101-108
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• 2018

This study was carried out to obtain baseline data on the causes of industrial accidents and their prevention by investigating structural models between the Shipyard workers' egogram ego-states (CP: Critical Parent, NP: Nurturing Parent, A: Adult, FC: Free Child, AC: Adapted Child), safe and unsafe behaviors, and industrial accidents (frequency/severity). In order to achieve this goal, 378 workers from 3 locations of major corporations in Geojedo Island and Ulsan took a questionnaire, which was then analyzed with a structural equation model using the SPSS 23.0 and AMOS 24 statistics package, and the main results of the study are as follows. First, NP and A's ego-states had a positive influence on safe behavior, AC's ego-state had a negative influence on safe behavior, and A's ego-state had the largest influence on safe behavior. Second, CP and AC's ego-states had a positive influence on unsafe behavior, and A's ego-state had a negative influence on unsafe behavior. AC's ego-state had the largest influence on unsafe behavior. Third, safe behavior did not have a significant influence on industrial accidents. However, unsafe behavior had a positive influence on industrial accident frequency and industrial accident severity, both sub-factors of industrial accidents. This study, despite its limitations, such as sampling limitations, has the following significance. First, this study verified that ego-state, a psychological characteristic, is an important factor for predicting unsafe behavior that induces industrial accidents. Second, in order to reduce industrial accidents, there is a need to stimulate the A ego-states, and promote continuous safety management and safety education to neutralize the AC ego-state. Third, previous studies were limited in the area of practical methods for reducing unsafe behaviors, but this study presents practical methods for reducing unsafe behaviors by verifying the structural relationship between safe/unsafe behaviors and industrial accidents by selecting ego-gram ego-states, variable personality theory, as an independent variable.

• Journal of the Korean Society of Safety
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• v.30 no.6
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• pp.26-33
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• 2015

This study suggests systematic procedures to improve safety policies on prevention of industrial accidents associated with industrial machines and devices. Specifically, new method of cause analysis of industrial accidents associated with industrial machines and devices is suggested and the related accident data are re-analyzed. Effectiveness of direct safety regulations such as safety certification, self-declaration of conformity, safety device regulation and safety inspection of industrial machines and devices are also analyzed. Based on those analysis results, transition from the current user-oriented safety device regulation to more balanced direct regulations on both manufacturer and user is suggested. Together with severity and frequency of industrial accidents, unit severity and unit frequency need to be taken into account to further assess the risk associated with a particular industrial machine or device. Balance between safety regulations will be realized by proper adjustment of lists of safety certification and inspection, and certification and inspection standards. This will also guarantee the maximum benefit over cost in such safety regulations.

• Journal of the Ergonomics Society of Korea
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• v.31 no.1
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• pp.137-142
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• 2012

Objective: The aim of this study is to investigate the characteristics of industrial accidents in shipbuilding industry. Background: As the accident frequency in shipbuilding industry is higher than those of other industries, it is important to grasp the accident characteristics of shipbuilding industry to reduce the accidents. Method: This paper aggregated some important accident report of the shipbuilding industry including industrial accident analysis of Korean government and drew some important accident characteristics of shipbuilding industry. Results: Accidents in Shipbuilding industry was reviewed in respect of accidents rate, accidents distribution by age, accidents by employed period, accidents severity, accidents type, accidents type by process, accidents caused by object, and hazards in process. Conclusion: Accident related indexes in shipbuilding were much higher than those of whole industry. Application: These results can be used to provide base information for more effective accident preventions in shipbuilding industry.

• Journal of the Korea Safety Management & Science
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• v.7 no.5
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• pp.59-67
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• 2005

The main objective of the statistical analysis about industrial accidents is to find out what is the dangerous factor in its own industrial field so that it is possible to prevent or decrease the number of the possible accidents by educating those who work in the fields for safety tools. However, so far, there is no technique of quantitative evaluation on danger. Almost all previous researches as to industrial accidents have only relied on the frequency analysis such as the analysis of the constituent ratio on accidents. As an application of data mining technique, this paper presents analysis on the efficiency of the CHAID algorithm to classify types of industrial accidents data and thereby identifies potential weak points in accident risk grouping.

• The Journal of the Korea Contents Association
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• v.19 no.12
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• pp.558-564
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• 2019

Using a sample of 220 employees in small and medium sized companies in Chungcheong and Gyeonggi provinces, we proposed that the companies' organizational communication on safety issues will positively influence employees' safety compliance and participation. And also, the companies' organizational communication will negatively influence the frequency of industrial accidents. The results of this study supported the hypotheses, implying that the frequency of industrial accidents will be decreasing if the company officially communicates with its employees in terms of the safety issues.

• Journal of the Korean Society of Safety
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• v.35 no.5
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• pp.59-65
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• 2020

For monitoring the status of industrial accidents, many statistical indexes have been developed and applied such as fatal rate, frequency rate, and severity rate. These accident indexes are measured by frequency and loss time according to the accidents in the individual industry level. However, it is less considered to use the index of identifying the industrial concentration of accidents in the holistic view. Thus, this study aims to suggest the accident concentration level among domestic industries through index analysis. The concentration level of industrial accidents is calculated by the accident composition of sub-industries. This concentration level shows whether an industry is comprised of a few sub-industries generating more accidents or an industry consists of sub-industries having the similar number of accidents. To this end, the concentration rate (CR) and concentration index (CI) are proposed to take a look at the industry composition of accidents by embracing the concept of market concentration indexes such as Hirschman-Herfindahl Index. As for the case study, four industries of mining, manufacturing, transportation, and other business (usually service) are analyzed in terms of indexes of accident rate, death(fatality) rate, and CR and CI of accident and death. Finally, we illustrate the positioning map that the accident concentration level is compared with the traditional accident frequency level among industries.

• Journal of the Korea Safety Management & Science
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• v.8 no.1
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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.