A modified human reliability analysis method for the estimation of human error probability in the offloading operations at oil terminals

2020 ◽  
Author(s):  
Renyou Zhang ◽  
Henry Tan ◽  
Waheed Afzal
Keyword(s):  
Reliability Analysis ◽  
Error Probability ◽  
Human Error ◽  
Analysis Method ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
Human Error Probability

An Application of CREAM for Human Reliability Analysis in Power System Switching Operation

2014 ◽  
Vol 584-586 ◽  
pp. 2585-2588 ◽  
Author(s):  
Jun Xi Tang ◽  
Ying Kai Bao ◽  
Li Cheng Wang ◽  
Chuang Xin Guo ◽  
Wen Hai Liu ◽  
...  
Keyword(s):  
Power System ◽  
Reliability Analysis ◽  
Human Error ◽  
Analysis Method ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
Switching Operation ◽  
Equipment Reliability ◽  
System Switching ◽  
Human Error Probability

Reliability is always one of the most focal points for the power system researchers. With the improvement of equipment reliability, human error has become a great threat to the power system security. But the human reliability analysis in power system does not get as much attention as it perhaps deserve. As a representative HRA method, the Cognitive Reliability and Error Analysis Method (CREAM) is cited in this paper. And it is applied to evaluate the human error probability of a simple switching operation case. This practice is a beneficial attempt to introduce HRA method into the power system reliability research and lay a foundation for the further explorations.

Human Reliability, Experience and Error Probability: A New Benchmark

2009 ◽  
Author(s):  
Romney B. Duffey ◽  
Tae Sung Ha
Keyword(s):  
Reliability Analysis ◽  
Error Probability ◽  
Human Error ◽  
Accident Risk ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
New Approach ◽  
Learning Hypothesis ◽  
Independent Assessment ◽  
Human Error Probability

In this paper, we apply a totally new approach to benchmark human reliability analysis, which is derived directly from the Universal Learning Curve (ULC) for homo-technological system (HTS) outcomes. We compare the latest second-generation predictions, based on the well-known and proven learning hypothesis, against some of the common Human Reliability Analysis (HRA) methods used to date for analyzing human reliability in transient and accident analysis. Therefore, we provide a straightforward, general and simple methodology for evaluating and predicting the Human Error Probability (HEP) in transients for accident risk prediction and reduction, as validated against all the available data, producing a completely independent assessment of the uncertainty.

HUMAN RELIABILITY ANALYSIS PADA OPERATOR GRINDING DAN WELDING GALANGAN KAPAL DENGAN PENDEKATAN COGNITIVE RELIABILITY AND ERROR ANALYSIS METHOD (CREAM)

2021 ◽  
Vol 11 (1) ◽  
pp. 59-65
Author(s):  
Satria Bagus Shaputra Satria ◽  
Nuzulia Khoiriyah ◽  
Wiwiek Fatmawati
Keyword(s):  
Error Analysis ◽  
Reliability Analysis ◽  
Human Error ◽  
Basic Method ◽  
Analysis Method ◽  
Human Reliability ◽  
Human Reliability Analysis

Abstrak, Daftar kasus kecelakaan kerja di galagan kapal yang terjadi selama 8 tahun terakhir dengan jumlah kasus tertinggi pada proses pekerjaan grinding dan welding. Kasus kecelakaan kerja tersebut disebabkan oleh kesalahan manusia atau human error. Pada penelitian ini menggunakan pendekatan Cogitive Reliability and Error Analysis Method (CREAM) untuk memprediksi dan mengurangi terjadinya human error. Pada metode ini dilakukan dengan dua cara yaitu basic method yang berfungsi untuk hanya mendapatkan nilai probabilitas kegagalan secara umum, sedangkan extend method berfungsi untuk mendapatkan nilai probabilitas kegagalan kognitif pada setiap task. Hasil penelitian menunjukkan bahwa faktor yang menurunkan keandalan operator dan mempengaruhi timbulnya human error pada operator grinding dan welding adalah faktor kondisi pekerjaan dan waktu dalam hari saat pekerjaan berlangsung. Nilai probabilitas error tertinggi pada proses pekerjaan grinding dan welding terdapat pada aspek kognitif interpretation, dengan masing-masing nilai CFP pada proses grinding yaitu sebesar 0,024 dan pada proses welding 0,006. Usulan perbaikan untuk mengurangi probabilitas human error pada proses grinding dan welding adalah pada kondisi pekerjaan dengan membutuhkan penerangan yang cukup saat bekerja didalam kapal, membutuhkan sirkulasi udara yang baik saat bekerja didalam kapal, dan membutuhkan peningkatan pengawasan kepada operator agar operator dapat bekerja dengan aman dan disiplin dalam bekerja. Serta membutuhkan pengoptimalan manajemen waktu dalam bekerja, agar operator dapat bekerja dengan baik dan memiliki waktu istirahat yang cukup.   Kata kunci : Human Error, Cogitive Reliability and Error Analysis Method (CREAM), Human Realiability Analysis (HRA).

scholarly journals Human reliability analysis in de-energization of power line using HEART in the context of Z-numbers

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0253827
Author(s):  
Hamed Aghaei ◽  
Mostafa Mirzaei Aliabadi ◽  
Farzaneh Mollabahrami ◽  
Kamran Najafi
Keyword(s):  
Reliability Analysis ◽  
Human Error ◽  
Critical Issue ◽  
Power Line ◽  
Electricity Distribution ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
Straightforward Method ◽  
Human Error Probability

Investigation reveals that a high percentage of incident causes are ascribed to some forms of human error. To effectively prevent incidents from happening, Human Reliability Analysis (HRA), as a structured way to represent unintentional operator contribution to system reliability, is a critical issue. Human Error Reduction and Assessment Technique (HEART) as a famous HRA technique, provides a straightforward method to estimate probabilities of human error based on the analysis of tasks. However, it faces varying levels of uncertainty in assigning of weights to each error producing condition (EPC), denoted as assessed proportion of affect (APOA), by experts. To overcome this limitation and consider the confidence level (reliability or credibility) of the experts, the current study aimed at proposing a composite HEART methodology for human error probability (HEP) assessment, which integrates HEART and Z-numbers short for, Z-HEART. The applicability and effectiveness of the Z-HEART has been illustrated in the de-energization power line as a case study. Furthermore, a sensitivity analysis is fulfilled to investigate the validity of the proposed methodology. It can be concluded that Z-HEART is feasible for assessing human error, and despite the methodological contributions, it offers many advantages for electricity distribution companies.

scholarly journals Systematic Human Reliability Analysis (SHRA): A New Approach to Evaluate Human Error Probability (HEP) in a Nuclear Plant

2020 ◽  
Vol 6 (1) ◽  
pp. 345-362
Author(s):  
Gianpaolo Di Bona ◽  
Domenico Falcone ◽  
Antonio Forcina ◽  
Luca Silvestri
Keyword(s):  
Emergency Management ◽  
System Reliability ◽  
Error Probability ◽  
Human Error ◽  
External Factors ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
New Approach ◽  
Internal And External Factors ◽  
Human Error Probability

Emergency management in industrial plants is a fundamental issue to ensure the safety of operators. The emergency management analyses two fundamental aspects: the system reliability and the human reliability. System reliability is the capability of ensuring the functional properties within a variability of work conditions, considering the possible deviations due to unexpected events. However, system reliability is strongly related to the reliability of its weakest component. The complexity of the processes could generate incidental situations and the worker appears (human reliability) to be the weakest part of the whole system. The complexity of systems influences operator’s ability to take decisions during emergencies. The aim of the present research is to develop a new approach to evaluate human error probability (HEP), called Systematic Human Reliability Analysis (SHRA). The proposed approach considers internal and external factors that affect operator’s ability. The new approach is based on Nuclear Action Reliability Assessment (NARA), Simplified Plant Analysis Risk Human Reliability (SPAR-H) and on the Performance Shaping Factors (PSFs) relationship. The present paper analysed some shortcomings related to literature approaches, especially the limitations of the working time. We estimated HEP, after 8 hours (work standard) during emergency conditions. The correlations between the advantages of these three methodologies allows proposing a HEP analysis during accident scenarios emergencies. SHRA can be used to estimate human reliability during emergencies. SHRA has been applied in a nuclear accident scenario, considering 24 hours of working time. The SHRA results highlight the most important internal and external factors that affect operator’s ability.

scholarly journals Human reliability analysis of high-temperature molten metal operation based on fuzzy CREAM and Bayesian network

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0254861
Author(s):  
Yaju Wu ◽  
Kaili Xu ◽  
Ruojun Wang ◽  
Xiaohu Xu
Keyword(s):  
High Temperature ◽  
Bayesian Network ◽  
Molten Metal ◽  
Error Probability ◽  
Human Error ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
Human Errors ◽  
Metallurgy Industry ◽  
Human Error Probability

Human errors are considered to be the main causation factors of high-temperature molten metal accidents in metallurgical enterprises. The complex working environment of high- temperature molten metal in metallurgical enterprises has an important influence on the reliability of human behavior. A review of current human reliability techniques confirms that there is a lack of quantitative analysis of human errors in high-temperature molten metal operating environments. In this paper, a model was proposed to support the human reliability analysis of high-temperature molten metal operation in the metallurgy industry based on cognitive reliability and error analysis method (CREAM), fuzzy logic theory, and Bayesian network (BN). The comprehensive rules of common performance conditions in conventional CREAM approach were provided to evaluate various conditions for high-temperature molten metal operation in the metallurgy industry. This study adopted fuzzy CREAM to consider the uncertainties and used the BN to determine the control mode and calculate human error probability (HEP). The HEP for workers involved in high-temperature melting in steelmaking production process was calculated in a case with 13 operators being engaged in different high-temperature molten metal operations. The human error probability of two operators with different control modes was compared with the calculation result of basic CREAM, and the result showed that the method proposed in this paper is validated. This paper quantified point values of human error probability in high-temperature molten metal operation for the first time, which can be used as input in the risk evaluation of metallurgical industry.

scholarly journals Quality Checks Logit Human Reliability (LHR): A New Model to Evaluate Human Error Probability (HEP)

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Gianpaolo Di Bona ◽  
Domenico Falcone ◽  
Antonio Forcina ◽  
Filippo De Carlo ◽  
Luca Silvestri
Keyword(s):  
System Reliability ◽  
Error Probability ◽  
Human Error ◽  
Working Hours ◽  
Working Time ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
New Approach ◽  
Accident Scenario ◽  
Human Error Probability

In the years, several approaches for human reliability analysis (HRA) have been developed. The aim of the present research is to propose a hybrid model to evaluate Human Error Probability (HEP). The new approach is based on logit-normal distribution, Nuclear Action Reliability Assessment (NARA), and Performance Shaping Factors (PSFs) relationship. In the research, shortcomings related to literature approaches are analyzed, especially the limitations of the working time. For this reason, PSFs after 8 hours (work standard) during emergency conditions were estimated. Therefore, the correlation between the advantages of these three methodologies allows proposing a HEP analysis during accident scenarios and emergencies; a fundamental issue to ensure the safety and reliability in industrial plants is emergency Mmnagement (EM). Applying EM methodology, two main aspects are analyzed: system reliability and human reliability. System reliability is strongly related to the reliability of its weakest component. During incidental situations, the weakest parts of the whole system are workers (human reliability) and accidental scenarios influence the operator’s ability to make decisions. This article proposes a new approach called Logit Human Reliability (LHR) that considers internal and external factors to estimate human reliability during emergencies. LHR has been applied in a pharmaceutical accident scenario, considering 24 hours of working time (more than 8 working hours). The results highlighted that the LHR method gives output data more in conformity with data banks than the conventional methods during the stress phase in an accident scenario.

scholarly journals Performer selection in Human Reliability analysis: D numbers approach

2019 ◽  
Vol 14 (3) ◽  
pp. 437-452 ◽  
Author(s):  
Jie Zhao ◽  
Yong Deng
Keyword(s):  
Reliability Analysis ◽  
Human Error ◽  
Multiple Criteria Decision Making ◽  
Experimental Result ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
Human Errors ◽  
Factors Influencing ◽  
D Numbers ◽  
Human Error Probability

Dependence assessment among human errors in human reliability analysis (HRA) is an significant issue. Many previous works discussed the factors influencing the dependence level but failed to discuss how these factors like "similarity of performers" determine the final result. In this paper, the influence of performers on HRA is focused, in addition, a new way of D numbers which is usually used to handle with the multiple criteria decision making (MCDM) problems is introduced as well to determine the optimal performer. Experimental result demonstrates the validity of proposed methods in choosing the best performers with lowest the conditional human error probability (CHEP) under the same circumstance.

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