• 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.

• 한국안전학회지
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• 제22권4호
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• pp.66-71
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• 2007

Human error is one of the major contributors to the railway accidents or incidents. In order to develop an effective countermeasure to remove or reduce human errors, a systematic analysis should be preferentially performed to identify their causes, characteristics, and types of human error induced in accidents or incidents. This paper introduces a case study for human error analysis of the railway accidents and incidents. For the case study, more than 1,000 domestic railway accidents or incidents that happened during the year of 2004 have been investigated and a detailed error analysis was performed on the selected 90 cases, which were obviously caused by human error. This paper presents a classification structure for human error analysis, and summarizes the analysis results such as causes of the events, error modes and types, related worker, and task type.

• 한국항공운항학회지
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• 제28권4호
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• pp.21-31
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• 2020

There are two to three helicopter accidents every year in Korea, representing 5.7 deaths per 100,000 flights. In this study, an analysis was conducted on helicopter accidents that occurred in Korea from 2005 to 2017. The accident analysis was based on the aircraft accident and incident report published by the Aircraft and Railway Accident Investigation Board. This Research analyzed the characteristics of accidents occurring in Korea caused by human error by pilots. Accident analysis was done by classifying the organization, flight mission, aircraft class, flight stage, accident cause, etc. Pilot's huan error was classified as Skill-based error, decision error and perceptual error in accordance with the HFACS taxonomy. The accidents caused by pilot's human error were classified into five categories: powerlines collision, loss of control, fuel exhaustion, unstable approach to reservoir, and elimination of tail rotor.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2006년도 추계학술대회 논문집
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• pp.1529-1535
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• 2006

Human error is one of the major contributors to the railway accidents or incidents. In order to develop an effective countermeasure to remove or reduce human errors, a systematic analysis should be preferentially performed to identify their causes, characteristics, and types of human error induced in accidents or incidents. This paper introduces a case study for human error analysis of the railway accidents and incidents. For the case study, more than 1,000 domestic railway accidents or incidents that happened during the year of 2004 have been investigated and a detailed error analysis was performed on the selected 90 cases, which were obviously caused by human error. This paper presents a classification structure for human error analysis, and summarizes the analysis results such as causes of the events, error modes and types, related worker, and task type.

• 선박안전
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• 통권27호
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• pp.25-36
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• 2009

Despite the development of the various navigational equipment, such as GPS, ARPA, ECDIS, AIS, VDR, and hull monitoring system, marine accidents are still a leading concern in shipping industry. For all accidents over the reporting period, approximately 60 to 80% of the accidents was involved in human error. It means that in each case, some events which were associated with human error initiated an accident, and those failures of human performance led to the failure to avoid an accident or mitigate it's consequences. However, the improvement and the effort on the maritime human error are still limited in an elementary step. The objective of this paper is to propose a modified Human Factors Analysis and Classification System (HFACS) model in order to analyse the collision accidents of tug-barge ship.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2015년도 추계학술대회
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• pp.199-201
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• 2015

Nowadays, the issue of maritime safety is an extremely important issue in the maritime industry and Human' Stress is one of the biggest causes of maritime accidents. The purpose of this study was to research and compare the risk marine accidents analysis methods and find the methods which used to analysis data of the human' stress and obtained the relationship between it and the risk of maritime accidents.

• 웰빙융합연구
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• 제7권1호
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• pp.27-33
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• 2024

Purpose: This study investigates human error accidents in the Korean railway sector, emphasizing the need for systematic management to prevent such incidents, which can have fatal consequences, especially in driving-related jobs. Research design, data and methodology: This paper analyzed data from the Aviation and Railway Accident Investigation Board and the Korea Transportation Safety Authority, examining 240 human error accidents that occurred over the last five years (2018-2022). The analysis focused on accidents in the driving, facility, electric, and control fields. Results: The findings indicate that the majority of human error accidents stem from negligence in confirmation checks, issues with work methods, and oversight in facility maintenance. In the driving field, errors such as signal check neglect and braking failures are prevalent, while in the facility and electric fields, the main issues are maintenance delays and neglect of safety measures. Conclusions: The paper concludes that human error accidents are complex and multifaceted, often resulting from a high workload on engineers and systemic issues within the railway system. Future research should delve into the causal relationships of these accidents and develop targeted prevention strategies through improved work processes, education, and training.

• 한국안전학회지
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• 제27권4호
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• pp.90-95
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• 2012

To prevent similar accidents with the basis of industrial accidents already occurred in industrial plants, it would be possible only after true causes are grasped. Unfortunately, however, most accident investigation carried out with the basis of legal regulation failed to grasp them so that similar accidents have been repeated without cease. This research aimed to find out differences between results from conventional accident investigation and those from human error analysis, and to draw out effective and practical counter-plans against industrial accidents occurred repeatedly in an autoglass manufacturing company. As for analysis, about 110 accident cases that occurred for last 7 years were collected, and by adopting the Comprehensive Human Error Analysis Technique developed by the previous researchers, not direct causes but basic fundamental causes that might induce workers to human errors were sought. In consequence, the result showed that facility factors or environmental factors such as improper layout, mistakes in engineering design, and malfunction of interlock system were authentic major accident causes as opposed to managerial factors such as personal carelessness or failure to wearing personal protective equipments, and/or improper work methods.

• 대한인간공학회지
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• 제29권2호
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• pp.241-248
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• 2010

In accident analysis, it is essential to understand the causal pathways of the accident. Although numerous accident models have been developed to help analysts understand how and why an accident occurs, most of them do not include all elements related to the accident in various fields. Thus analysis of human error accidents in railway operations using these existing models may be possible, but inevitably incomplete. For a more thorough analysis of the accidents in railway operations, a more exhaustive model of accident causation is needed. This paper briefly reviews four recent accident causation models, and proposes a new model that overcomes the limitations of the existing models for the analysis of human error accidents in railway operations. In addition, the usefulness and comprehensiveness of the proposed model is briefly tested by explaining 12 railway accident cases with the model. The proposed accident causation model is expected to improve understanding of how and why an accident/incident occurs, and help prevent analysts from missing any important aspect of human error accidents in railway operations

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2004년도 Asia Navigation Conference
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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.