• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.08a
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• pp.139-145
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• 2004

It is well known that human errors is involved in most of maritime accidents. For the purpose of reducing the influence of human elements on maritime activities, it is necessary to identify the human unsafe acts in those activities. The commonly used methods in identification of human unsafe acts are maritime accident statistics or case analysis. With the statistics data, people could roughly identify what kinds of unsafe acts or human errors have played active role in the accident, however, they often neglected some active unsafe acts while overestimated some mini-unsafe acts because of the inherent shortcoming of the methods. There should be some more accurate approaches for human error identification in maritime accidents. In this paper, the application of technique called grey relational analysis (GRA) into the identification of human unsafe acts is presented. GRA is used to examine the extent of connections between two digits by applying the, methodology of departing and scattering measurement to actual distance measurement. Based on the statistics data of maritime accidents occurred in Chinese waters in last 10years, the relationship between the happening times of maritime accidents and that of unsafe acts are established with GRA. In accordance with the value of grey relational grade, the identified main human unsafe acts involved in maritime accidents are ranked in following orders: improper lookout, improper use of radar and equivalent equipment, error of judgment, act not in time, improper communication, improper shiphandling, use of unsafe speed, violating the rule and ignorance of good seamanship. The result shows that GRA is an effective and practical technique in improving the accuracy of human unsafe acts identification.

• 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 Korean Society for Aviation and Aeronautics
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• v.25 no.4
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• pp.161-169
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• 2017

The Human Factors Analysis and Classification System (HFACS) is a general human error framework originally developed and tested within the U.S. military as a tool for investigating and analyzing the human causes of aviation accidents. Based upon Reason's (1990) model of latent and active failures, HFACS addresses human error at all levels of the system, including the condition of aircrew and organizational factors. As a result, this study aims to examine the influence between the latent conditions based on HFACS. This study seeks to verify the factors of "Organizational Influence" effecting the "Precondition for Unsafe Acts" of HFACS. The results of empirical analysis demonstrated that the organizational influence had a positive influence on precondition for unsafe act, especially the "Organizational Climate" of organizational influence had even greater influence on precondition for unsafe acts.

• Journal of the Korean Society of Safety
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• v.29 no.4
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• pp.132-139
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• 2014

According to the increase of foreign laborers at domestic construction sites, it's necessary to research in terms of the unsafe acts of both Korean and foreign laborers in order to prevent construction disasters. The objective of this study is to clarify the characteristics and the improvement priority of the unsafe acts using IPA(Importance-Performance Analysis). The result of this study showed which items of unsafe acts are identify difference between Korean and foreign laborers. Moreover, the result of IPA also showed items of unsafe acts that needed the immediate improvement for each one. Especially there are two items, i.e. equipment malfunction and wrong handling of hand tools, which both Korean and foreign laborers think simultaneous those needs improvement. The results can be utilized to plan and to improve the safety management and education at a site considering the characteristics of foreign laborers.

• Journal of the Ergonomics Society of Korea
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• v.25 no.4
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• pp.137-144
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• 2006

The goal of this study is to find out correlation between Driver's Unsafe acts(errors and violations) and Personality types. The experiment was performed on 180 subjects, men and women between 20's and 60's having experience in driving for 6 months at least. Personality types of the subjects were classified by MBTI(Myers-Briggs Type Indicator) GS type and Driver's unsafe acts were measured by KDBQ(Korean Driver Behavior Questionnaire) based on Reason's DBQ(Driver Behavior Questionnaire). The result of experiment showed several facts about the relation. The first is that the drivers of P (Perceiving) type commit more violations and slips than drivers of J(Judging) type. The second is that in the comparison among attitude indexes(EP, EJ, IP, IJ) the drivers of EP(Extroversions - Perceiving) commit more violations than other type drivers. Finally, only men of P(Perceiving) type commits more violations than men of J(Judging). Based on these facts, it is possible to use Personality types as a device to prevent unsafe acts in various fields for driver selection and accident prevention training classified by Personality types etc.

• Journal of the Korean Society of Safety
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• v.37 no.3
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• pp.52-59
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• 2022

Conventionally, all the unsafe acts by human beings in relation to industrial accidents have been regarded as unintentional human errors. Exceptionally, however, in the cases with fatalities, seriously injured workers, and/or losses that evoked social issues, attention was paid to violating related laws and regulations for finding out some people to be prosecuted and given judicial punishments. As Heinrich stated, injury or loss in an accident is quite a random variable, so it can be unfair to utilize it as a criterion for prosecution or punishment. The present study was conducted to comprehend how categorizing intentional violations in unsafe acts might disrupt conventional conclusions about the industrial accident process. It was also intended to seek out the right direction for countermeasures by examining unsafe acts comprehensively rather than limiting the analysis to human errors only. In an analysis of 150 industrial accident cases that caused fatalities and featured relatively clear accident scenarios, the results showed that only 36.0% (54 cases) of the workers recognized the situation they confronted as risky, out of which 29.6% (16 cases) thought of the risk as trivial. In addition, even when the risks were recognized, most workers attempted to solve the hazardous situations in ways that violated rules or regulations. If analyzed with a focus on human errors, accidents can be attributed to personal deviations. However, if considered with an emphasis on safety rules or regulations, the focus will naturally move to the question of whether the workers intentionally violated them or not. As a consequence, failure of managerial efforts may be highlighted. Therefore, it was concluded that management should consider unsafe acts comprehensively, with violations included in principle, during accident investigations and the development of countermeasures to prevent future accidents.

• Journal of the Korean Society of Safety
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• v.9 no.2
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• pp.26-32
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• 1994

It is quite similar in the current automated works likewise in the past manual works that single trivial human error and/or unsafe acts may lead to serious industrial accidents. Though the traditional approach for accident prevention focused on the serious injuries or losses, that was misleaded by failure of accident perception. As Heinrich pointed out, there are still enormous numbers of unsafe acts or near-misses before a real accident happen. Thus, for industrial accident prevention, a research on unsafe acts was committed. With accident data occurred during the last decade, statistics were analyzed for extracting behavioral characteristics. After that, a practical method Integrating AHP and statistics which shows possible accident factors and their priority at an individual factory was suggested. A computer program was developed also.

• Safety and Health at Work
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• v.8 no.3
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• pp.267-275
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• 2017

Background: The mining industry is known worldwide for its highly risky and hazardous working environment. Technological advancement in ore extraction techniques for proliferation of production levels has caused further concern for safety in this industry. Research so far in the area of safety has revealed that the majority of incidents in hazardous industry take place because of human error, the control of which would enhance safety levels in working sites to a considerable extent. Methods: The present work focuses upon the analysis of human factors such as unsafe acts, preconditions for unsafe acts, unsafe leadership, and organizational influences. A modified human factor analysis and classification system (HFACS) was adopted and an accident predictive fuzzy reasoning approach (FRA)-based system was developed to predict the likelihood of accidents for manganese mines in India, using analysis of factors such as age, experience of worker, shift of work, etc. Results: The outcome of the analysis indicated that skill-based errors are most critical and require immediate attention for mitigation. The FRA-based accident prediction system developed gives an outcome as an indicative risk score associated with the identified accident-prone situation, based upon which a suitable plan for mitigation can be developed. Conclusion: Unsafe acts of the worker are the most critical human factors identified to be controlled on priority basis. A significant association of factors (namely age, experience of the worker, and shift of work) with unsafe acts performed by the operator is identified based upon which the FRA-based accident prediction model is proposed.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.5
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• pp.161-168
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• 2019

Construction industry is becoming more advanced, but safety accidents are not decreasing and unsafe act (UA) and human errors (HE) are the main causes of safety accidents. Therefore, this study aims to analyze the relationships between unsafe acts and human errors for construction accident prevents. Specifically, the Correlation Analysis is used to quantify 24 combinations of the relationship between the UA and HE. Then, the Kano Model, and Timko Satisfied Coefficient was utilized to find 6 combinations for construction accident prevention plans. As the result of Timko Satisfied Coefficient, an interview was conducted with three safety managers and 6 safety prevention plan is proposed. Through these results, it is expected that the combination of 24 accidents will be basic data of safety management. Especially, the proposed safety prevention plans considering the characteristics of 6 combinations with high correlation can contribute to prevention of safety accidents at the construction site.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.12
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• pp.1711-1716
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• 2018

Unlike conventional transmission and distribution lines, catenary system for operating electric railway vehicles are composed of multi-conductor groups (feeder line, contact wire, messenger wire, protection wire) and are used for railway employees, public or passengers in the station yards. Electric shock hazards are exposed and electric shocks such as death or serious injury are occurring in electric railway vehicles, railway high-voltage distribution lines, and catenary system. In order to analyze the types of electric shock accidents on railway by systematic approach method, we modeled 'unsafe behavior classification' method using swiss cheese model. Based on this method, we derived the type of electric shock accidents about railway accidents during the last 5 years by analyzing the frequency of occurrence of human errors and unsafe acts, laws and regulations related to violations, and so on.