bibtype C - Conference Paper (international conference)
ARLID 0543435
utime 20240103225938.3
mtime 20210624235959.9
title (primary) (eng) Integrating the human factor in FMECA-based risk evaluation through Bayesian networks
specification
page_count 6 s.
media_type P
serial
ARLID cav_un_epca*0543434
ISBN 978-84-09-25132-2
title Modelling for Engineering & Human Behaviour 2020
page_num 24-29
publisher
place Valencia
name The Universitat Politècnica de València
year 2020
keyword risk management
keyword evaluation
keyword Bayesian Network
author (primary)
ARLID cav_un_auth*0398866
name1 Carpitella
name2 Silvia
institution UTIA-B
full_dept (cz) Matematická teorie rozhodování
full_dept (eng) Department of Decision Making Theory
department (cz) MTR
department (eng) MTR
country IT
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0256480
name1 Izquierdo
name2 J.
country ES
author
ARLID cav_un_auth*0329423
name1 Plajner
name2 Martin
institution UTIA-B
full_dept (cz) Matematická teorie rozhodování
full_dept Department of Decision Making Theory
department (cz) MTR
department MTR
full_dept Department of Decision Making Theory
country CZ
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101228
name1 Vomlel
name2 Jiří
institution UTIA-B
full_dept (cz) Matematická teorie rozhodování
full_dept Department of Decision Making Theory
department (cz) MTR
department MTR
full_dept Department of Decision Making Theory
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2021/MTR/carpitella-0543435.pdf
cas_special
abstract (eng) Risk management processes play a fundamental part in any business context and rely on accurate conduction of the risk assessment stage. Risks are commonly evaluated according to the preliminary definition of suitable parameters mainly aimed at highlighting their severity and the frequency of occurrence. However, it may be interesting to integrate the human factor as a parameter of evaluation, being human activity directly related with many risks of diverse nature. This contribution develops the traditional Failure Modes, Effects and Criticality Analysis (FMECA) [1] for quantitative risk analysis from a Bayesian Network (BN)-based perspective, which reveals to be useful to make more accurate predictions about parameters’ values. The main purpose consists in providing a framework for analysing causal relationships for risk evaluation and deriving probabilistic inference among significant risk factors. These parameters are represented by linguistic variables and include the human factor as a key element of analysis.
action
ARLID cav_un_auth*0410795
name Mathematical Modelling Conference in Engineering & Human Behaviour 2020
dates 20200708
mrcbC20-s 20200710
place Valencia
country ES
RIV JS
FORD0 20000
FORD1 20200
FORD2 20205
reportyear 2022
num_of_auth 4
presentation_type PR
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0320678
confidential S
arlyear 2020
mrcbU14 SCOPUS
mrcbU24 PUBMED
mrcbU34 WOS
mrcbU63 cav_un_epca*0543434 Modelling for Engineering & Human Behaviour 2020 978-84-09-25132-2 24 29 Valencia The Universitat Politècnica de València 2020