TY - GEN
T1 - Applications of Bayesian networks in chemical and process industries
T2 - 29th European Safety and Reliability Conference, ESREL 2019
AU - Zerrouki, Hamza
AU - Estrada-Lugo, Hector Diego
AU - Smadi, Hacene
AU - Patelli, Edoardo
N1 - Publisher Copyright:
Copyright © 2019 European Safety and Reliability Association.
PY - 2020
Y1 - 2020
N2 - Despite technological advancements, chemical and process industries are still prone to accidents due to their complexity and hazardous installations. These accidents lead to significant losses that represent economic losses and most importantly human losses. Risk management is one of the appropriate tools to guarantee the safe operations of these plants. Risk analysis is an important part of risk management, it consists of different methods such as Fault tree, Bow-tie, and Bayesian network. The latter has been widely applied for risk analysis purposes due to its flexible and dynamic structure. Bayesian networks approaches have shown a significant increase in their application as shown by in the publication in this field. This paper summarizes the result of a literature review performed on Bayesian network approaches adopted to conduct risk assessments, safety and risk analyses. Different application domains are analysed (i.e. accident modelling, maintenance area, fault diagnosis) in chemical and process industries from the year 2006 to 2018. Furthermore, the advantages of different types of Bayesian networks are presented.
AB - Despite technological advancements, chemical and process industries are still prone to accidents due to their complexity and hazardous installations. These accidents lead to significant losses that represent economic losses and most importantly human losses. Risk management is one of the appropriate tools to guarantee the safe operations of these plants. Risk analysis is an important part of risk management, it consists of different methods such as Fault tree, Bow-tie, and Bayesian network. The latter has been widely applied for risk analysis purposes due to its flexible and dynamic structure. Bayesian networks approaches have shown a significant increase in their application as shown by in the publication in this field. This paper summarizes the result of a literature review performed on Bayesian network approaches adopted to conduct risk assessments, safety and risk analyses. Different application domains are analysed (i.e. accident modelling, maintenance area, fault diagnosis) in chemical and process industries from the year 2006 to 2018. Furthermore, the advantages of different types of Bayesian networks are presented.
KW - Bayesian networks
KW - Chemical industry
KW - Dynamic Bayesian Networks
KW - Object-Oriented Bayesian networks
KW - Process industry
KW - Risk analysis
UR - http://www.scopus.com/inward/record.url?scp=85089186611&partnerID=8YFLogxK
U2 - 10.3850/978-981-11-2724-30914-cd
DO - 10.3850/978-981-11-2724-30914-cd
M3 - Conference contribution
AN - SCOPUS:85089186611
T3 - Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019
SP - 3122
EP - 3129
BT - Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019
A2 - Beer, Michael
A2 - Zio, Enrico
PB - Research Publishing Services
Y2 - 22 September 2019 through 26 September 2019
ER -