• Journal of the Korean Institute of Gas
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• v.6 no.4 s.18
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• pp.1-7
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• 2002

Human errors can take place in all levels that include the design, production, construction, operation and maintenance of plant facilities. It was found that the causes were concerned with the effects of human error. This study verified characteristics of the on-site operators and error mechanism, and used the classifying sheet to analyze human error that occurred in process. Also, by applying the ASEP(Accident Sequence Evaluation Program) HRA(Human Reliability Analysis) procedure, the algorithm to estimate the HEP and the ASEP HEP program to analyze human error in the plant were developed. If it is built in on-site, possible human error incident will be prevented and the systematic human error prevention strategy will be devised.

• Safety and Health at Work
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• v.13 no.3
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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.

• Journal of the Korean Institute of Gas
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• v.4 no.2 s.10
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• pp.52-57
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• 2000

This paper suggests the evaluation sheet to ensure the objective and detailed information based on a classification table of PIF (Performance Influencing Factor). And this paper shows the results of HEP(Human Error Probability), using a quantitative method with the evaluated data as a result of estimating the likelihood of . human errors in the gas industry facility together with the evaluation sheet. Finally, these results are programmed to be operated in personal computer so that field workers an apply it in easy and convenient manner. The results of this study offer two key benefits; sharing reliable information on human errors with the Data Base and establishing a strategy to reduce human errors as well as to improve working proficiency.

• Journal of the Korean Society of Safety
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• v.18 no.2
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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.

• Journal of the Korean Institute of Gas
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• v.11 no.2 s.35
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• pp.60-64
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• 2007

Chemical Process industry in Korea has over 30 year's of history and is likely to face potential incidents. The traditional risk analysis and control system in Chemical Process industry focuses on mechanical defects, overlooking the human performance control. Although development of automation technology and controlling technology was necessary, human decision factor is essential to preventing accidents in the Chemical Process. Almost all serious accidents take place when inappropriate humanperformance and mechanical defects of safety equipments simultaneously occurs. The AHRA(Advanced Human Reliability Analyzer) software has been developed to collect failure data and analyze human error probability (Reliability) in Chemical Process Industry in Korea. This paper describes the HRA analysis result of PIF(Performance Influencing Factor) evaluation, HEP(Human Error Probability) and root cause of accidents by applying a Chemical Process Industry related accident data. This analysis result should present a scheme that, by controlling human error factor other than putting safety management funds into the machinery in plants, can reduce cost and maximize the safety in Chemical Process Industry.

• Nuclear Engineering and Technology
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• v.45 no.2
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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.

• Proceedings of the Korean Institute of Industrial Safety Conference
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• 2002.05a
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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)

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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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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• v.53 no.2
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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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• v.54 no.1
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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.