Application of Fuzzy HEART and expert elicitation for quantifying human error probabilities in LPG refuelling station

Kumar, Akshay; Rajakarunakaran, S.; Prabhu, Vignesh

doi:10.1016/j.jlp.2017.04.021

Cited by 33 publications

(10 citation statements)

References 31 publications

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“…These authors also presented an extended methodology of HEART which integrated with type-2 Fuzzy to cope with the experts' elicitations uncertainty in the APOA appraisal [34]. Maniram Kumar et al [35] used Fuzzy logic combining with HEART to overcome the inaccuracy of experts' preferences in assigning the relative strength of EPCs over GTT. Mirzaei Aliabadi [27] proposed a human error analysis composite HEART and Intuitionistic Fuzzy to find HEP in furnace start-ups tasks.…”

Section: State Of the Artmentioning

confidence: 99%

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

et al. 2021

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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.

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Section: State Of the Artmentioning

confidence: 99%

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

et al. 2021

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“…Continuing with modern methodologies, see Table 12, fuzzy models try to assess the human behavior; a representative model of this group is the Human Error and Assessment Technique (HEART), assuming that the reliability of any task performance may be modified by the influence of Error Promoting Conditions (EPCs), this model is applied to detect human errors in a LPG (Liquefied Petroleum Gas) refueling station [142]. An additional representative method of this group is the CREAM-BN, an upgrade of the systemic Cognitive Reliability and Error Analysis Method (CREAM), using Bayesian networks to determine the probability of human failure considering behavior components: Strategic, tactical, opportunistic, or scramble, this model is applied in maintenance tasks, in-field operations, and in chemical plant incidents [143][144][145].…”

Section: Hdsp Mksk Gt-stmentioning

confidence: 99%

“…HEART [142] Human Error and Assessment Technique. The human behavior and reliability of any operator task performance may be modified by the influence of Error Promoting Conditions (EPCs).…”

Section: Fuzzy Basedmentioning

confidence: 99%

Analysis and Characterization of Risk Methodologies Applied to Industrial Parks

et al. 2020

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It is important to evaluate the risks in industrial parks and their processes due to the consequences of major accidents and especially the domino effect. Scientific works present a wide possibility of models to deal with these situations. In this work, based on the information extracted from the scientific literature, six groups of risk methodologies are defined, analyzed, and characterized with methods that cover the standards, preventive, probabilistic, traditional, modern, and dynamic evaluation that are applied or could be used in industrial parks. It also tries to achieve the objective of determining which are more appropriate if the possible situations and causes that can produce an accident are taken into account, identifying and evaluating them with characteristics of simultaneity and immediacy, determining the probability of an accident occurring with sufficient advance in time to avoid it under the use of a working operational procedure. There is no definitive methodology, and it is necessary that they complement each other, but considering the proposed objective, the integrated application of traditional methodologies together with the management of safety barriers, the dynamic evaluation of risks, and the inclusion of machine learning systems could fulfill the proposed objective.

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“…Una de las características principales de las técnicas de la segunda generación es que pueden ser aplicadas para evaluar la probabilidad de error humano en las industrias [22]. El método SHERPA llamado así por sus siglas en inglés Systematic Human Error Reduction and Prediction Approach.…”

Section: Revisión De La Literaturaunclassified

Cuantificación del error humano en la cadena de suministro: caso de estudio en los servicios de transporte terrestre

Saavedra-Robinson¹,

Páez-Sarmiento²,

Ramírez³

2020

revuin

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Esta investigación presenta un acercamiento desde la ergonomía cognitiva en la determinación del error humano en el sector logístico, particularmente para el caso del transporte terrestre de carga. Para ello se aplicaron los métodos de Systematic Human Error Reduction and Prediction Approach –SHERPA y Success Likelihood Index Method –SLIM en tres empresas participantes del estudio. Se identificaron errores en la generación del costo del servicio (T1), en el ingreso de datos del servicio (T2), en la notificación a los clientes de las novedades del servicio (T3) y en la preparación de la documentación para los conductores (T4). Se cuantificaron los errores cuya probabilidad de ocurrencia oscilaron entre un 24,8% y 34,2%. Sedeterminó la fiabilidad de cada error como un sistema independiente, en cuyo caso el resultado arrojado para las tareas T1, T2 y T3 fue del 80% y del 75% para T4.

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Application of Fuzzy HEART and expert elicitation for quantifying human error probabilities in LPG refuelling station

Cited by 33 publications

References 31 publications

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

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

Analysis and Characterization of Risk Methodologies Applied to Industrial Parks

Cuantificación del error humano en la cadena de suministro: caso de estudio en los servicios de transporte terrestre

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