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.

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.

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 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.

A Method for Marine Human Error Probability Estimate: APJE-SLIM

2011 ◽  
Vol 97-98 ◽  
pp. 825-830 ◽  
Author(s):  
Yong Tao Xi ◽  
Chong Guo
Keyword(s):  
Collision Avoidance ◽  
Human Error ◽  
Shipping Industry ◽  
Human Reliability ◽  
Combined Method ◽  
Probability Estimate ◽  
Human Errors ◽  
Performance Shaping Factors ◽  
Industry Research ◽  
Human Error Probability

Safety is the eternal theme in shipping industry. Research shows that human error is the main reason of maritime accidents. Therefore, it is very necessary to research marine human errors, to discuss the contexts which caused human errors and how the contexts effect human behavior. Based on the detailed investigation of human errors in collision avoidance behavior which is the most key mission in navigation and the Performance Shaping Factors (PSFs), human reliability of mariners in collision avoidance was analyzed by using the integration of APJE and SLIM. Result shows that this combined method is effective and can be used for the research of maritime human reliability.

Revisiting the FPSO São Mateus Accident From a Human Reliability Perspective Using Phoenix HRA Methodology

2020 ◽  
Author(s):  
Marilia A. Ramos ◽  
Alex Almeida ◽  
Marcelo R. Martins
Keyword(s):  
Human Error ◽  
Oil And Gas ◽  
Risk Estimation ◽  
Petroleum Industry ◽  
Oil And Gas Industry ◽  
Qualitative Assessment ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
Human Errors ◽  
Gas Industry

Abstract Several incidents in the offshore oil and gas industry have human errors among core events in incident sequence. Nonetheless, human error probabilities are frequently neglected by offshore risk estimation. Human Reliability Analysis (HRA) allows human failures to be assessed both qualitatively and quantitatively. In the petroleum industry, HRA is usually applied using generic methods developed for other types of operation. Yet, those may not sufficiently represent the particularities of the oil and gas industry. Phoenix is a model-based HRA method, designed to address limitations of other HRA methods. Its qualitative framework consists of three layers of analysis composed by a Crew Response Tree, a human response model, and a causal model. This paper applies a version of Phoenix, the Phoenix for Petroleum Refining Operations (Phoenix-PRO), to perform a qualitative assessment of human errors in the CDSM explosion. The CDSM was a FPSO designed to produce natural gas and oil to Petrobras in Brazil. On 2015 an explosion occurred leading to nine fatalities. Analyses of this accident have indicated a strong contribution of human errors. In addition to the application of the method, this paper discusses its suitability for offshore operations HRA analyses.

UNCERTAINTY OF HUMAN ERROR AND FUZZY APPROACH TO HUMAN RELIABILITY ANALYSIS

2006 ◽  
Vol 14 (01) ◽  
pp. 111-129 ◽  
Author(s):  
B. J. KIM ◽  
RAM R. BISHU
Keyword(s):  
Reliability Analysis ◽  
Nuclear Power ◽  
Power Plants ◽  
Human Error ◽  
Critical Factor ◽  
Fuzzy Approach ◽  
Human Reliability ◽  
Human Reliability Analysis ◽  
Human Errors ◽  
Fuzzy Logic Approach

Human error is regarded as a critical factor in catastrophic accidents such as disasters at nuclear power plants, air plane crashes, or derailed trains. Several taxonomies for human errors and methodologies for human reliability analysis (HRA) have been proposed in the literature. Generally, human errors have been modeled on the basis of probabilistic concepts with or without the consideration of cognitive aspects of human behaviors. Modeling of human errors through probabilistic approaches has shown a limitation on quantification of qualitative aspects of human errors and complexity of attributes from circumstances involved. The purpose of this paper is to investigate the methodologies for human reliability analysis and introduce a fuzzy logic approach to the evaluation of human interacting system's reliability. Fuzzy approach could be used to estimate human error effects under ambiguous interacting environments and assist in the design of error free work environments.

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