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

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.

Author(s):  
Gianpaolo Di Bona ◽  
Domenico Falcone ◽  
Antonio Forcina ◽  
Luca Silvestri

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.


Author(s):  
Romney B. Duffey ◽  
Tae Sung Ha

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.


PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0254861
Author(s):  
Yaju Wu ◽  
Kaili Xu ◽  
Ruojun Wang ◽  
Xiaohu Xu

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.


2014 ◽  
Vol 584-586 ◽  
pp. 2585-2588 ◽  
Author(s):  
Jun Xi Tang ◽  
Ying Kai Bao ◽  
Li Cheng Wang ◽  
Chuang Xin Guo ◽  
Wen Hai Liu ◽  
...  

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.


PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0253827
Author(s):  
Hamed Aghaei ◽  
Mostafa Mirzaei Aliabadi ◽  
Farzaneh Mollabahrami ◽  
Kamran Najafi

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.


Author(s):  
Yustina Ngatilah ◽  
Endang Pudji W ◽  
Rr Rochmoeljati ◽  
Tranggono Tranggono

Seluruh industri pasti memiliki keinginan untuk memiliki zero accident. Namun pada kenyataannya banyak perusahaan yang memiliki angka kecelakaan yang tinggi tiap tahunnya. Human Reliability Assessment merupakan salah satu metode untuk memberi usulan alternatif pengurangan terhadap kecelakaan kerja yang terjadi. Dimana langkah yang digunakan yakni mengumpulkan data kecelakaan kerja,data Task Analysis Sistem dan data identifikasi kegagalan. Pengolahan yang dilakukan yakni dengan penggambaran kecelakaan kerja menggunakan Fault Tree Analysis,kemudian kuantifikasi nilai Human Error Probability dengan metode Human Error And Reduction Technique dan pada akhirnya akan ditemukan usulan alternatif pengurangan kecelakaan kerja. Hasil dari penelitian ini adalah mengidentifikasi kesalahan manusia yang menimbulkan kecelakaan kerja. Kesalahan karyawan tersebut antara lain posisi pemotongan kurang benar dengan probabilitas tertinggi yaitu 0,728, untuk yang lain seperti gagal memposisikan saat pengambilan material, salah posisi dalam melakukan prosedur,tidak fokus dalam melakukan proses,tidak memperhatikan posisi kayu dan terburu-buru dalam melakukan prosedur probabilitasnya dibawah 0,728.


2014 ◽  
Vol 644-650 ◽  
pp. 5664-5667
Author(s):  
Chen Shang ◽  
Xin Hui Ma ◽  
Jing Peng Chen

According to the characteristics of space launch day, the common performance conditions (CPC) were improved. After the CPC were weighted, the value of the performance influence index was presented. And based on the modified CREAM method, a human reliability assessment was given. Consequently, the outcomes of this work can provide the human error probability and data base for safety assessment of space launch site.


2019 ◽  
Vol 14 (3) ◽  
pp. 437-452 ◽  
Author(s):  
Jie Zhao ◽  
Yong Deng

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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