Applications of Bayesian networks in chemical and process industries: A review



Zerrouki, H, Estrada-Lugo, HD, Smadi, H and Patelli, E ORCID: 0000-0002-5007-7247
(2020) Applications of Bayesian networks in chemical and process industries: A review. .

[img] Text
Overview_of_BN_in_chemical_and_process_industries.pdf - Accepted Version

Download (824kB) | Preview

Abstract

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.

Item Type: Conference or Workshop Item (Unspecified)
Depositing User: Symplectic Admin
Date Deposited: 11 Sep 2019 15:05
Last Modified: 07 Sep 2022 07:30
DOI: 10.3850/978-981-11-2724-30914-cd
URI: https://livrepository.liverpool.ac.uk/id/eprint/3054267