• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2008년도 춘계학술대회
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• pp.93-100
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• 2008

In this paper, we propose the application of the Human Factors Analysis and Classification System(HFACS) to analyze an aircraft accident data. 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. It was examined that HFACS reliably accommodate all human causal factors associated with the commercial accidents. We found that the HFACS could be used as a reliable tool for investigating aircraft accidents including a single accident analysis.

• 한국안전학회지
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• 제35권4호
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• pp.64-73
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• 2020

As Korean government and safety-related organizations make continuous efforts to reduce the number of industrial accidents, accident rate has steadily declined since 2010, thereby recording 0.48% in 2017. However, the number of fatalities due to industrial accidents was 1,987 in 2017, which means that more efforts should be made to reduce the number of industrial accidents. As an essential activity for enhancing the system safety, accident analysis can be effectively used for reducing the number of industrial accidents. Accident analysis aims to understand the process of an accident scenario and to identify the plausible causes of the accident. Accident analysis offers useful information for developing measures for preventing the recurrence of an accident or its similar accidents. However, it seems that the current practice of accident analysis in Korean manufacturing companies takes a simplistic accident model, which is based on a linear and deterministic cause-effect relation. Considering the actual complexities underlying accidents, this would be problematic; it could be more significant in the case of human error-related accidents. Accordingly, it is necessary to use a more elaborated accident model for addressing the complexity and nature of human-error related accidents more systematically. Regarding this, HFACS(Human Factors Analysis and Classification System) can be a viable accident analysis method. It is based on the Swiss cheese model and offers a range of causal factors of a human error-related accident, some of which can be judged as the plausible causes of an accident. HFACS has been widely used in several work domains(e.g. aviation and rail industry) and can be effectively used in Korean industries. However, as HFACS was originally developed in aviation industry, the taxonomy of causal factors may not be easily applied to accidents in Korean industries, particularly manufacturing companies. In addition, the typical characteristics of Korean industries need to be reflected as well. With this issue in mind, we developed HFACS-K as a method for analyzing accidents happening in Korean industries. This paper reports the process of developing HFACS-K, the structure and contents of HFACS-K, and a case study for demonstrating its usefulness.

• International Journal of Internet, Broadcasting and Communication
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• 제12권4호
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• pp.1-10
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• 2020

Safety can be defined as being maintained or reduced to a level below which the possibility of human or physical harm can be tolerated through continuous identification of risks and safety risk management. FAA, EASA, IATA and Boeing, major organizations that conduct research and analysis for aviation safety around the world, report that about 70 percent of aviation accidents are caused by human factors, which have led to a surge in interest in human factors-induced accident prevention activities around the world. As part of this purpose, the FAA in the U.S. is raising awareness among aviation workers by publicizing the 12 human errors (Boeing, 2016), which account for the largest part of aviation accidents under the theme of Dirty Dozen, to prevent aviation accidents. Therefore, based on the domestic helicopter accidents reported to the Air Railroad Accident Investigation Committee from 2007 until recently, this study aims to use HFACS to extract human factors for the six recent helicopter accidents in Korea, analyze the extracted human factors in conjunction with the Dirty Dozen concept, and then present measures to prevent accidents by item.

• 해양환경안전학회지
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• 제21권5호
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• pp.515-523
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• 2015

본 연구에서는 10년간(2001 2010) IMCA에 보고된 DP 선박 LOP(Loss of Position)사고 612건에서 인적오류에 의한 사고 103건을 확인하여 이를 HFACS로 분류하였다. 그리고 이를 베이지안 네트워크에 적용하여 인적오류의 조건부 확률을 확인해 보았다. 그 결과 103건의 인적오류관련 사고는 모두 불안전한 행동에 의해서 발생하였고 이들 중 기술 기반 오류가 70건(68.00 %)으로 가장 큰 인적오류 비율을 차지하였다. 기술 기반 오류 중에서는 부주의한 DP 선박 운용 60건(58.3%), 절차 미 준수 8건(7.8%)이었고, 의사결정 오류에 의한 잘못된 조종이 21건(20.8%)을 차지하였다. 이러한 HFACS 분류의 베이지안 네트워크 적용을 통해서는 불안전한 감독(68%)이 불안전한 행동의 가장 큰 잠재적 요인으로 작용하고 있다는 것을 확인 할 수 있었다. 결론적으로 HFACS와 연계한 베이지안 네트워크는 인적오류를 분석하는 데 유용한 도구임을 확인 할 수 있었고, 분석 결과를 바탕으로 DP 선박안전 운용을 위한 정책, 내부 관계, 훈련등과 같은 인적오류를 경감 및 제거하기 위한 권고 9가지를 제안하였다.

• 대한인간공학회지
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• 제30권1호
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• pp.137-150
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• 2011

Nationally and internationally reported statistics on marine accidents show that 80% or more of all marine accidents are caused fully or in part by human error. According to the statistics of marine accident causes from Korean Maritime Safety Tribunal(KMST), operating errors are implicated in 78.7% of all marine accidents that occurred from 2002 to 2006. In the case of the collision accidents, about 95% of all collision accidents are caused by operating errors, and those human error related collision accidents are mostly caused by failure of maintaining proper lookout and breach of the regulations for preventing collision. One way of reducing the probability of occurrence of the human error related marine accidents effectively is by investigating and understanding the role of the human elements in accident causation. In this paper, causal factors/root causes classification systems for marine accident investigation were reviewed and some typical human error analysis methods used in shipping industry were described in detail. This paper also proposed a human error analysis method that contains a cognitive process model, a human error analysis technique(Maritime HFACS) and a marine accident causal chains, and then its application to the actual marine accident was provided as a case study in order to demonstrate the framework of the method.

• 한국항해항만학회지
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• 제41권5호
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• pp.303-318
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• 2017

In the shipping industry, it is well known that around 80 % or more of all marine accidents are caused fully or at least in part by human error. In this regard, the International Maritime Organization (IMO) stated that the study of human factors would be important for improving maritime safety. Consequently, the IMO adopted the Casualty Investigation Code, including guidelines to assist investigators in the implementation of the Code, to prevent similar accidents occurring again in the future. In this paper, a process of the human factors investigation is proposed to provide investigators with a guide for determining the occurrence sequence of marine accidents, to identify and classify human error-inducing underlying factors, and to develop safety actions that can manage the risk of marine accidents. Also, an application of these investigation procedures to a collision accident is provided as a case study This is done to verify the applicability of the proposed human factors investigation procedures. The proposed human factors investigation process provides a systematic approach and consists of 3 steps: 'Step 1: collect data & determine occurrence sequence' using the SHEL model and the cognitive process model; 'Step 2: identify and classify underlying human factors' using the Maritime-Human Factor Analysis and Classification System (M-HFACS) model; and 'Step 3: develop safety actions,' using the causal chains. The case study shows that the proposed human factors investigation process is capable of identifying the underlying factors and indeveloping safety actions to prevent similar accidents from occurring.

• 한국항공운항학회지
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• 제10권1호
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• pp.9-20
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• 2002

In aviation, it is important to analyse and classify human error in detail. Because human error has been implicated in 70 or 80% of aviation accidents in literature review. But, there is little detailed classification and research of human error. In this study, Objectives are to establish human error model by classifying types of human error in detail and also to analyse human factors by using the established model. Analysis of the data uses Korea Aviation Incidents Reporting System(GYRO). The resulting from actual analysis, there is a some difference between flight steps for human error occurrence and types of human error are different according to the aviation personnel(pilot, ATC controller).

• International Journal of Aeronautical and Space Sciences
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• 제16권3호
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• pp.451-462
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• 2015

Safety is the first priority in civil aviation, and so the International Civil Aviation Organization (ICAO) has introduced and mandated the use of Safety Management Systems (SMS) by airlines, airports, air traffic services, aircraft maintenance organizations, and training organizations. The aircraft manufacturing industry is the last for which ICAO has mandated the implementation of SMS. Since SMS is a somewhat newer approach for most manufacturers in the aviation industry, they hardly believe in the value of implementing SMS. The management of safety risk characteristics that occur during early aircraft development stages and the systematic linkage that the safety risk has to do with an aircraft in service could have a significant influence on the safe operation and life cycle of the aircraft. This paper conducts a case analysis of the McDonnell Douglas MD-11 accident/incident to identify the root causes and safety risk levels, and also verified why aircraft manufacturing industry should begin to adopt SMS in order to prevent aircraft accident.

• 대한인간공학회지
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• 제35권3호
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• pp.143-153
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• 2016

Objective: The purposes of this study are to survey needs for changing accident investigation from blaming to systems approach and to briefly summarize systems-based accident analysis techniques. Background: In modern complex socio-technical systems, accidents are caused by a variety of contributing factors including human, technical, organizational, social factors, not by just a single violation or error of a specific actor, but accidents investigation used to be focused on the incorrect action of individuals. A new approach investigating causes of accidents as a symptom of a deficient system is required. Method: This study was mainly based on survey of literatures related to accidents, accidents investigation, which included academic journals, newspapers, etc. Results: This study showed that accidents investigation of Korea focusing on blaming is problematic. This was confirmed by two concepts of migration and hindsight bias frequently found in accident causation studies, and an attribute of accidents having varying causes. This was illustrated with an example of Sewol ferry capsizing accident. Representative systems-based accident analysis models including Swiss cheese model, AcciMap, HFACS, FRAM and STAMP were briefly introduced, which can be used in systematic accidents investigations. Finally, this study proposed a procedure for establishing preventive measures of accidents, which was composed of two steps: public inquiry and devising preventive measures. Conclusion: A new approach considering how safety-critical components such as technical and social elements, and their interactions lead to accidents is needed for preventing reoccurrence of similar accidents in complex socio-technical systems. Application: The results would be used as a reference or guideline when the safety relevant governmental organizations investigate accidents.

• 한국항해항만학회지
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• 제41권5호
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• pp.259-268
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• 2017

Formal Safety Assessment (FSA) has been mostly implemented on the hardware aspects of vessels. Although there are guidelines regarding human error FSAs, there have not been many assessments in such areas. To this end, this study seeks to use precedent studies for the safe operation of DP vessels, conducting an FSA regarding human error of DP LOP (Loss of Position) incidents. For this, the study referred to precedent studies for the frequency of DP LOP incidents caused by human errors, adding the severity of LOP incidents, and then applying them to the Bayesian network. As a result, the study was able to confirm that among DP LOP incidents caused by human errors, the drive-off from skill-based errors was 74.3% and the drive-off from unsafe supervision was 50.5%. Based on such results, RCOs (Risk Control Options) were devised through a brainstorming session with experts coming up with proposals including providing mandatory DPO training, installing DP simulator on the vessels, drawing up measures to understanding the procedures for safe operation of DP vessels. Moreover, it was found that mandatory DPO training is reasonable in terms of cost benefits and that while installing a DP simulator is not suitable in terms of cost benefits, it can significantly reduce risks when operating DP vessels.