• 한국가스학회지
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• 제6권4호
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• pp.1-7
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• 2002

인적 오류(human error)는 공장설비의 설계, 제작, 건설, 운전, 유지$\cdot$보수의 모든 단계에서 발생할 수 있으며 사고의 대부분이 인적 오류의 영향과 관계되어 있는 것으로 조사되고 있다. 본 연구에서는 현장의 작업자 행동 특성 및 오류 메커니즘을 확인하고, 평가분류 쉬트를 활용하여 공정에서 발생하는 인적 오류를 분석하였다. 또한 ASEP HRA 절차를 이용하여 인적 오류 확률(HEP) 산정 알고리즘을 구축하여 현장에서 쉽게 인적 오류를 분석할 수 있는 ASEP HEP 프로그램을 개발하였다. 이를 이용하여 화학공장에서의 가능한 인적 오류사고를 예방하고 보다 체계적인 인적 오류 방지대책을 수립할 수 있다고 판단된다.

• Safety and Health at Work
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• 제13권3호
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• pp.326-335
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• 2022

Background: One of the important actions for enhancing human reliability in any industry is assessing human error probability (HEP). The HEART technique is a robust tool for calculating HEP in various industries. The traditional HEART has some weaknesses due to expert judgment. For these reasons, a hybrid model is presented in this study to integrate HEART with Best-Worst Method. Materials Method: In this study, the blasting process in an iron ore mine was investigated as a case study. The proposed HEART-BWM was used to increase the sensitivity of APOA calculation. Then the HEP was calculated using conventional HEART formula. A consistency ratio was calculated using BWM. Finally, for verification of the HEART-BWM, HEP calculation was done by traditional HEART and HEART-BWM. Results: In the view of determined HEPs, the results showed that the mean of HEP in the blasting of the iron ore process was 2.57E-01. Checking the full blast of all the holes after the blasting sub-task was the most dangerous task due to the highest HEP value, and it was found 9.646E-01. On the other side, obtaining a permit to receive and transport materials was the most reliable task, and the HEP was 8.54E-04. Conclusion: The results showed a good consistency for the proposed technique. Comparing the two techniques confirmed that the BWM makes the traditional HEART faster and more reliable by performing the basic comparisons.

• 한국가스학회지
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• 제4권2호
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• pp.52-57
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• 2000

본 연구에서는 자료를 통한 국내 가스산업시설의 인적오류에 관한 산업재해를 분석하고 국외에서 발전된 정량화 방법을 이용하여 인적 오류 가능성을 예측할 수 있도록, 먼저 PIF(Performance Influencing Factor)분류구조를 바탕으로 보다 객관적이고 정확한 자료를 얻기 위해 평가 Sheet를 제시하였다. 그리고 평가 Sheet를 이용하여 가스산업시설의 인적 오류변수들을 평가하고, 평가 자료를 가지고 정량화 기법을 이용하여 HEP(Human Error Probability)를 산출하게 된다. 마지막으로, 보다 현장 작업자들이 편하고 쉽게 적용시킬 수 있도록 프로그램화를 시켰다. 본 연구의 결과로써 신뢰성 있는 인적오류 D/B를 구축함으로써 이를 공유할 수 있으며, 그리고 인간의 능률을 현저히 향상시킴과 동시에 인적오류감소 전략을 수립하는데 많은 도움이 될 것이다.

• 한국안전학회지
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• 제18권2호
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• pp.104-118
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• 2003

It has been criticized that conventional human reliability analysis (HRA) methodologies for probabilistic safety assessment (PSA) have been focused on the quantification of human error probability (HEP) without detailed analysis of human cognitive processes such as situation assessment or decision-making which are crticial to successful response to emergency situations. This paper introduces a new human reliability analysis (HRA) methodology, AGAPE-ET (A guidance And Procedure for Human Error Analysis for Emergency Tasks), focused on the qualitative error analysis of emergency tasks from the viewpoint of the performance of human cognitive function. The AGAPE-ET method is based on the simplified cognitive model and a taxonomy of influencing factors. By each cognitive function, error causes or error-likely situations have been identified considering the characteristics of the performance of each cognitive function and influencing mechanism of PIFs on the cognitive function. Then, overall human error analysis process is designed considering the cognitive demand of the required task. The application to an emergency task shows that the proposed method is useful to identify task vulnerabilities associated with the performance of emergency tasks.

• 한국가스학회지
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• 제11권2호통권35호
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• pp.60-64
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• 2007

한국에서는 석유화학 산업의 역사가 30년 이상이 되어 시설이 노후화되기 시작하여 잠재적인 사고의 위험 가능성이 높아지고 있다. 지금까지의 석유화학 산업에서의 전통적인 위험성 평가와 시스템의 제어는 기계적인 결함에만 중점을 두었기 때문에 인간의 행동을 제어하는 것은 간과하여 왔다. 자동화 기술과 제어기술의 발전도 필요하지만 인간의 의사 결정 요소가 석유화학산업에서 사고를 예방하는데 필수적이다. 거의 모든 심각한 사고는 인간 행동과 안전 장비의 기계적인 결함이 동시에 부적당할 때 발생한다. 진보적인 인간의 신뢰성 분석 소프트웨어는 실패 데이터를 수집하고, 한국의 화학 산업에서 인간의 오류 확률을 분석하기 위해 개발되었다. 이 논문에서는 Root cause Analysis를 통한 결과와 PIF(Performance Influencing Factor) 평가 결과를 보여준다.

• Nuclear Engineering and Technology
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• 제45권2호
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• pp.151-164
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• 2013

A key input for the assessment of Human Error Probabilities (HEPs) with Human Reliability Analysis (HRA) methods is the evaluation of the factors influencing the human performance (often referred to as Performance Shaping Factors, PSFs). In general, the definition of these factors and the supporting guidance are such that their evaluation involves significant subjectivity. This affects the repeatability of HRA results as well as the collection of HRA data for model construction and verification. In this context, the present paper considers the TAsk COMplexity (TACOM) measure, developed by one of the authors to quantify the complexity of procedure-guided tasks (by the operating crew of nuclear power plants in emergency situations), and evaluates its use to represent (objectively and quantitatively) task complexity issues relevant to HRA methods. In particular, TACOM scores are calculated for five Human Failure Events (HFEs) for which empirical evidence on the HEPs (albeit with large uncertainty) and influencing factors are available - from the International HRA Empirical Study. The empirical evaluation has shown promising results. The TACOM score increases as the empirical HEP of the selected HFEs increases. Except for one case, TACOM scores are well distinguished if related to different difficulty categories (e.g., "easy" vs. "somewhat difficult"), while values corresponding to tasks within the same category are very close. Despite some important limitations related to the small number of HFEs investigated and the large uncertainty in their HEPs, this paper presents one of few attempts to empirically study the effect of a performance shaping factor on the human error probability. This type of study is important to enhance the empirical basis of HRA methods, to make sure that 1) the definitions of the PSFs cover the influences important for HRA (i.e., influencing the error probability), and 2) the quantitative relationships among PSFs and error probability are adequately represented.

• 한국산업안전학회:학술대회논문집
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• 한국안전학회 2002년도 춘계 학술논문발표회 논문집
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• pp.231-236
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• 2002

급속한 산업의 발달에 따른 화학산업 시설의 공정 및 설비의 세분화는 대규모의 잠재 위험성을 증가시키며, 산업현장에서는 인간의 불안전한 행동 및 상태의 잠재위험으로 인한 중대재해 사고의 우려가 더 한층 증가하고 있다.(중략)

• 한국재난정보학회:학술대회논문집
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• 한국재난정보학회 2022년 정기학술대회 논문집
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• pp.227-228
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• 2022

전통적인 HRA(Human Reliability Analysis)방법은 특정 애플리케이션 또는 산업을 염두에 두고 있으며. 또한 이러한 방법은 종종 복잡하며, 시간이 많이 걸리고 적용하는 데 비용이 많이 들며 직접 비교하기에는 적합하지 않다. 제안된 HFHM(Human Factors Hazard Model: 인적 요인 위험 모델)은 기검증되고 시간 테스트를 거친 FTA(Fault Tree Analysis:결함 트리 분석)및 ETA(Event Tree Analysis:이벤트 트리 분석)의 확률 분석 도구 및 새로 개발된 HEP(Human Error Probability:인적 오류 확률)예측 도구와 통합되고, 인간과 관련된 PSF(Performance Shaping Factors:성능 형성 요인)를 중심으로 새로운 접근 방식으로 개발되었다. 인간-시스템은 상호작용으로 인한 재난사고 가능성을 모델링하는 위험분석 접근법 HFHM은 다음과 같은 상용 소프트웨어 도구 내에서 예시되고 자동화된다. HFHM에서 생성된 데이터는 SE 분석가 및 설계에 대한 표준화된 가이드로 사용될 수 있다. 본 연구에서는 인적 위험을 예측하는 이 새로운 접근 방식을 통해, 전체 시스템에 대한 포괄적인 재난안전 분석을 가능하게 한다.

• Nuclear Engineering and Technology
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• 제53권2호
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• pp.368-375
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• 2021

The performance time of human operators has been recognized as a key aspect of human reliability in socio-complex systems, including nuclear industries. Because of the importance of the time factor, most existing human reliability assessment methods provide ways to quantify human error probabilities (HEPs) that are associated with the performance time. To quantify such kinds of HEPs, it is crucial to rationally predict the length of time required and time available and compare them. However, there have not been detailed guidelines that identify the critical cue presentation time or initial time of human performance, which is important to calculate the time information. In this paper, we introduce a time-related HEP calculation technique with a decision algorithm that determines the critical cue and its timing. The calculation process is presented with the application examples. It is expected that the proposed algorithm will reduce the variability in the time-related reliability assessment and strengthen the scientific evidence of the assessment process. The detailed description is provided in the technical report KAERI/TR-7607/2019.

• Nuclear Engineering and Technology
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• 제54권1호
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• pp.110-116
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• 2022

Human failure event (HFE) dependency analysis is a part of human reliability analysis (HRA). For efficient HFE dependency analysis, a maximum number of minimal cut sets (MCSs) that have HFE combinations are generated from the fault trees for the probabilistic safety assessment (PSA) of nuclear power plants (NPPs). After collecting potential HFE combinations, dependency levels of subsequent HFEs on the preceding HFEs in each MCS are analyzed and assigned as conditional probabilities. Then, HFE recovery is performed to reflect these conditional probabilities in MCSs by modifying MCSs. Inappropriate HFE dependency analysis and HFE recovery might lead to an inaccurate core damage frequency (CDF). Using the above process, HFE recovery is performed on MCSs that are generated with a non-zero truncation limit, where many MCSs that have HFE combinations are truncated. As a result, the resultant CDF might be underestimated. In this paper, a new method is suggested to incorporate HFE recovery into the MCS generation stage. Compared to the current approach with a separate HFE recovery after MCS generation, this new method can (1) reduce the total time and burden for MCS generation and HFE recovery, (2) prevent the truncation of MCSs that have dependent HFEs, and (3) avoid CDF underestimation. This new method is a simple but very effective means of performing MCS generation and HFE recovery simultaneously and improving CDF accuracy. The effectiveness and strength of the new method are clearly demonstrated and discussed with fault trees and HFE combinations that have joint probabilities.