• 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.

• Nuclear Engineering and Technology
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• 제54권3호
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• pp.948-958
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• 2022

Since reliability and security of man-machine system increasingly depend on reliability of human, human reliability analysis (HRA) has attracted a lot of attention in many fields especially in nuclear engineering. Dependence assessment among human tasks is a important part in HRA which contributes to an appropriate evaluation result. Most of methods in HRA are based on experts' opinions which are subjective and uncertain. Also, the dependence influencing factors are usually considered to be constant, which is unrealistic. In this paper, a new model based on Dempster-Shafer evidence theory (DSET) and fuzzy number is proposed to handle the dependence between two tasks in HRA under uncertain and dynamic situations. First, the dependence influencing factors are identified and the judgments on the factors are represented as basic belief assignments (BBAs). Second, the BBAs of the factors that varying with time are reconstructed based on the correction BBA derived from time value. Then, BBAs of all factors are combined to gain the fused BBA. Finally, conditional human error probability (CHEP) is derived based on the fused BBA. The proposed method can deal with uncertainties in the judgments and dynamics of the dependence influencing factors. A case study is illustrated to show the effectiveness and the flexibility of the proposed method.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 춘계학술대회 논문집
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• pp.502-506
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• 2007

Railway accidents/incidents occur because of many reasons. Human error by the railway staff or personnel takes a major part of those reasons. In order to reduce and prevent railway accidents/incidents, appropriate measures should be developed to remove root causes induced in human error. A systematic study for analysing causes of human errors and for developing an effective management is necessary. Detailed analysis of the railway traffic signaller's tasks should be preferentially performed for this purpose. This paper introduces the results of analysis for the types and characteristics of the railway traffic signaller's tasks. As a result of the analysis, the railway traffic signaller's tasks can be decomposed into 24 tasks in total, and also be divided into the general task and the emergency task. The railway traffic signaller's tasks are characterized to require continual confirmation and observation activities, and sometimes immediate decision and action.

• 한국가스학회지
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• 제18권4호
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• pp.68-75
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• 2014

독성가스시설에서 대형사고로 인한 손실을 감소시키기 위해서는 인적요소를 제어하고, 평가하는 것이 필요하다. 기존의 안전성 평가는 기계적 결함이나 시스템의 위험이 주로 강조되어 왔으며, 인적오류를 관리하는 평가방법이 부족하여 본 연구에서는 독성가스시설의 사고관리 상황에서 인적오류를 구성하는 수행영향인자 분류체계를 제안하고자 하였다. 이를 위해 주요 수행영향인자 분류체계의 유형을 수집하여 검토와 분석을 한 후 4가지(작업자 특성, 시스템, 직무특성 및 직무환경)로 나누고, 독성가스시설의 상황적 특성과 직무특성 및 작업환경을 고려하여 수행영향인자를 선택하였다. 이로 부터 인적오류의 평가에 사용하기 적절한 수행영향인자 체계를 구축하고, 구축한 수행영향인자 분류체계를 독성가스시설에서 발생하였던 사고 사례분석을 통해 적용성을 검토하였다.

• Journal of Animal Science and Technology
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• 제64권3호
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• pp.531-538
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• 2022

In Italy, buffalo mozzarella is a largely sold and consumed dairy product. The fraudulent adulteration of buffalo milk with cheaper and more available milk of other species is very frequent. In the present study, Fourier transform infrared spectroscopy (FTIR), in combination with multivariate analysis by partial least square (PLS) regression, was applied to quantitatively detect the adulteration of buffalo milk with cow milk by using a fully automatic equipment dedicated to the routine analysis of the milk composition. To enhance the heterogeneity, cow and buffalo bulk milk was collected for a period of over three years from different dairy farms. A total of 119 samples were used for the analysis to generate 17 different concentrations of buffalo-cow milk mixtures. This procedure was used to enhance variability and to properly randomize the trials. The obtained calibration model showed an R² ≥ 0.99 (R² cal. = 0.99861; root mean square error of cross-validation [RMSEC] = 2.04; R² val. = 0.99803; root mean square error of prediction [RMSEP] = 2.84; root mean square error of cross-validation [RMSECV] = 2.44) suggesting that this method could be successfully applied in the routine analysis of buffalo milk composition, providing rapid screening for possible adulteration with cow's milk at no additional cost.

• 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.

• 한국항행학회논문지
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• 제23권1호
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• pp.8-19
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• 2019

조종사는 휴먼에러(human error)를 감소시키기 위한 방법들 중 하나로 체크리스트를 사용하여 항공의 안전에 도움이 되는 도구로 사용하고 있다. 하지만 복잡한 체크리스트는 경험이 부족한 학생 조종사들에게는 체크리스트가 작성된 본연의 목적과 다르게 안전에 위해 요인이 될 수 있다. 본 연구는 우선 학생조종사들이 사용하는 정상 체크리스트의 구성항목들을 단계 별로 살펴보았다. 이를 통해 체크리스트를 구성하는 요인들이 휴먼에러를 구성하는 요인들과 어떤 상관관계를 내포하는지 학생조종사들을 대상으로 한 사례연구를 통해 규명하고자 하였다. 탐색적 사례연구를 통해 다음과 같은 시사점을 제안하였다. 학생조종사들이 preflight inspection 체크리스트 점검을 수행함에 있어 기체에 대한 외부점검을 효율적으로 수행하도록 기체구조 또는 동력계통에 대한 전문지식 강화가 필요하다. 비행 시마다 조종사뿐만 아니라 해당 비행기의 정비 담당자가 외부점검을 실시하여 더블체크를 하는 재확인 절차를 통하여 안전을 증진시켜야 할 것이다.

• 한국항공운항학회지
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• 제25권4호
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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.

• 대한인간공학회지
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• 제31권1호
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• pp.261-269
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• 2012

Objective: The aim of this study is to develop an analysis method to extract plausible types of errors when using a smart mobile in nuclear power plants. Background: Smart mobiles such as a smart-phone and a tablet computer(smart-pad) are to be introduced to the various industries. Nuclear power plant like APR1400 already adopted many up-to-date digital devices within its main control room. With this trend, various types of smart mobiles will be inevitably introduced to the nuclear field in the near future. However nuclear power plants(NPPs) should be managed considering a big risk as a result of the trend not only economically but also socially compared to the other industrial systems. It is formally required to make sure to reasonably prevent the all hazards due to the introduction of new technologies and devices before the application to the specific tasks in nuclear power plants. Method: We define interaction segments(IS) as a main architect of interaction description, and enumerate all plausible error segments(ES) for a part of design evaluation of digital devices. Results: We identify various types of interaction errors which are coped with reasonably by interaction design using smart mobiles. Conclusion: According to the application result of the proposed method, we conclude that the proposed method can be utilized to specify the requirements to the human error hazards in digital devices, and to conduct a human factors review during the design of digital devices. Application: The proposed method can be applied to predict the human errors of the tasks related to the digital devices; therefore we can ensure the safety to apply the digital devices to be introduced to NPPs.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2019년도 추계학술대회
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• pp.265-265
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• 2019

선박을 조종할 때 발생하는 항해사의 인적오류로 인해 해양사고는 매년 꾸준히 발생하고 있다. 이 연구의 목적은 해기사가 선박조종에 나타난 행동으로 인해 발생하는 인적오류에 의해서 야기 될 수 있는 선박충돌사고를 예방하여 항행안전을 도모하는 것이다. 해기사의 행동으로 발생하는 인적오류를 관리 할 수 있는 방법은 두 가지이다. 개인 접근법과 시스템 접근법으로 구분되며, 이는 상황인식이론과 라스무센의 행동이론으로 적용되었다. 이를 과거 해양사고에서 발생한 인적오류를 조사하고, 선박조종시뮬레이터를 이용하여 실험을 진행해 이 두 가지 행동 특성을 식별하였다. 두 가지 해기사 인적오류 특성을 분석하였으며, 이를 기반으로 추후에는 대응 방법을 제안하고자 한다.