Over the years, many techniques have been developed for human reliability analysis (HRA). The main weakness of traditional HRA approaches is the use of a simple classification scheme without a link to a model of cognition in terms of mental processes. The present work is an attempt in this direction through a particular hybrid probabilistic model. The human error in industrial emergency model aims to develop an integrated methodological approach useful in critical infrastructures during an emergency condition. The proposed method, starting from the integration of existing techniques, develops a very flexible tool, able to take into account the main external and internal factors responsible of human error in emergency conditions. The model is able to estimate the evolution of human behavior and error following the evolution of the emergency scenario. The final result is a simulation model that calculates the contextualized human error probability, through which it is possible to estimate a realistic and detailed scenario of the conditions during the emergency management. © 2017 ASM International
A Hybrid Probabilistic Model for Evaluating and Simulating Human Error in Industrial Emergency Conditions (HEIE)
DE FELICE, Fabio;FALCONE, Domenico;ZOMPARELLI, Federico;SILVESTRI, Alessandro
2017-01-01
Abstract
Over the years, many techniques have been developed for human reliability analysis (HRA). The main weakness of traditional HRA approaches is the use of a simple classification scheme without a link to a model of cognition in terms of mental processes. The present work is an attempt in this direction through a particular hybrid probabilistic model. The human error in industrial emergency model aims to develop an integrated methodological approach useful in critical infrastructures during an emergency condition. The proposed method, starting from the integration of existing techniques, develops a very flexible tool, able to take into account the main external and internal factors responsible of human error in emergency conditions. The model is able to estimate the evolution of human behavior and error following the evolution of the emergency scenario. The final result is a simulation model that calculates the contextualized human error probability, through which it is possible to estimate a realistic and detailed scenario of the conditions during the emergency management. © 2017 ASM InternationalI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
