• Proceedings of the Safety Management and Science Conference
• /
• 2008.04a
• /
• pp.93-100
• /
• 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.

• Journal of Advanced Navigation Technology
• /
• v.25 no.3
• /
• pp.256-266
• /
• 2021

Domestic and foreign studies point to human factors as the main cause of unmanned aerial vehicle accidents, and HFACS is introduced as a technique to effectively analyze these human factors. Until now, domestic and foreign cases of analyzing the human factors of unmanned aerial vehicle accidents using HFACS were mainly targeted by military unmanned aerial vehicles, which can be used as an objective cause identification and similar accident prevention tool. In particular, identifying the focus of HFACS application considering the performance and operation conditions of domestic civilian unmanned aerial vehicles is expected to greatly help identify the cause and prevent recurrence in the event of an accident. Based on HFACS version 7.0, this study analyzed the accident investigation report data conducted by Korea Aviation and Railway Accident Investigation Board to identify the focus of HFACS application that can be used for domestic civilian unmanned aircraft accident investigations.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.25 no.4
• /
• pp.161-169
• /
• 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.

• 한국항공운항학회:학술대회논문집
• /
• 2016.05a
• /
• pp.108-116
• /
• 2016

Structured Checklist of System Aviation Safety Oversight had been categorized by HFACS. In this Study, Findings of Aviation Safety oversight, have been categorized by HFACS. Thus, those two categorized results have difference in incongruity clause that can be concluded that Structured Checklist has lack of elements. Therefore, we are able to identify validity and suitability of checklist that need to be restructured and redeveloped by performing test analysis through this study.

• Journal of the Korean Society of Safety
• /
• v.35 no.4
• /
• pp.64-73
• /
• 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.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.32 no.1
• /
• pp.1-9
• /
• 2024

The unmanned aerial vehicle industry has developed a lot, but the possibility of accidents is increasing due to potential risks. In this study, SHELL models and HFACS were used to analyze unmanned aerial vehicle accidents in the UK and to identify the main causes and characteristics of accidents. The main cause analyzed by the SHELL model was identified as an abnormality in the alarm system. The main cause of the accident analyzed by HFACS was identified as the technical environment. The common cause identified by the SHELL model and HFACS was identified as a mechanical problem of unmanned aerial vehicles. This is due to the lack of accurate information or functionality of the alarm system in the operator interface, which often prevents the operator from responding to sensitive information. Therefore, in order to prevent civil UAV accidents, the stability and reliability of the system must be secured through regular inspections of the UAV system and continuous software updates. In addition, an ergonomic approach considering human interfaces is needed when developing technologies.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.25 no.4
• /
• pp.195-203
• /
• 2017

Around 70% of domestic aircraft accidents in helicopter aircraft. The causal factors of the helicopter accidents are identified as human factors. People have focused mostly on unsafe acts to prevent the accident. The accidents should be analysed on human factors to reduce accident. The unsafe acts can be managed effectively if the latent failures were identified through the HFACS. This paper is to introduce about the latent failure classified by the HFACS and provide the analysis regarding the latent failure of the helicopters by the aviation safety advisors through the interviews.

• International Journal of Internet, Broadcasting and Communication
• /
• v.12 no.4
• /
• pp.1-10
• /
• 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.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.24 no.2
• /
• pp.59-67
• /
• 2016

The checklist currently used for Aviation safety inspection performed by ASIs consists of inspection groups and multiple items, it does not have structured hierarchy system which required to efficiently process aviation safety analysis. On this study, through mapping taxonomy of HFACS onto current checklist to secure structured hierarchy system and present a specification on systematic frequency and severity to perform safety risk assessment of detected hazard.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.28 no.2
• /
• pp.63-70
• /
• 2020

Many organizations apply reactive safety management to prevent the same or similar types of accidents by through investigation and analysis of the accident cases. Although research on investigation techniques has contributed a lot to the objective results of safety accidents and the preparation of countermeasures, many accident investigation techniques currently in use treat accidents from a linear perspective, revealing limitations in reflecting current systems dominated by complexity and uncertainty. In order to overcome these limitations, this study will review recent studies and concepts from a system safety perspective and predict future research trends through a case analysis of aviation accident. The models used in the analysis are STAMP, HFACS, and FRAM, and the characteristics of each technique are presented so that analysts who perform related tasks in the field can refer to them.