Human reliability and cognitive processing

Filho, Salvador Ávila; Cerqueira, Ivone; Santino, Carine Nogueira

doi:10.1016/b978-0-12-819650-2.00001-8

Cited by 1 publication

(2 citation statements)

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“…There is a high probability of initiating high-impact, low-visibility failures during the progressive stress stage in an accident occurrence. Cognitive functions are altered: memory, attention, logical reasoning, perception, and decision, that is why they react with the inclusion of auxiliary memory through notes, documents, mind maps, and safety systems, to achieve successful decisions [13,44]. The indicators were identified and subjected to analysis as to the degree of importance for an industry sector leader in an emergency, according to the presentation in Table 1.…”

Section: Variables and Indicators For The Analysis Of The Industry Le...mentioning

confidence: 99%

“…The response capacity both from the leader and from his/her team in a crisis scenario requires, in addition to technological safety resources, properly planned barriers, technical knowledge, and cognitive-behavioral processing. In addition, spaces for discussion during the planning of the facilities, simulations in training, and essential compositions in the formation of leaders of highly complex industries [12,13].…”

Section: Introductionmentioning

confidence: 99%

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Development of Adaptive Neuro-Fuzzy Inference System for Assessing Industry Leadership in Accident Situations

et al. 2022

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Petroleum activity is characterized as a high-risk activity due to the probability of accidents with material and human losses. The leaders of this segment assume, besides the complex routine tasks, the challenge of making assertive decisions during an accident. This study aims to present an evaluation model of the Industry Leadership Index for Emergencies Situations (ILIE), using the Adaptive Neuro-Fuzzy System (ANFIS). The model was composed of 4 input variables, namely: knowledge, behavior, skill, and attitude; and one output variable, Industry Leadership. The data collection took place in petroleum production units in Brazil, with a sample of 151 respondents through the application of a survey. The observed data were treated in an Excel tabulator and used in the development of the ANFIS model. From this model, it was possible to carry out simulations to predict the impact, which the increase or decrease in the value of each input variable can influence the leader's profile. The model performed satisfactorily in the Root of the Mean Square Error (RMSE) analysis, being 0.199 in data training and 1.217 in data verification. The results suggest that the ANFIS method can be successfully applied to establish a model to analyze industry leaders prepared for assertive responses in crisis scenarios. .

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Section: Variables and Indicators For The Analysis Of The Industry Le...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%