Process Safety Assessment Considering Multivariate Non-linear Dependence Among Process Variables

Nonlinear dependencies among highly correlated variables of a multifaceted process system pose significant challenges for process safety assessment. The copula function is a flexible statistical tool to capture complex dependencies and interactions among process variables in the causation of process...

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Main Authors: Ghosh, A., Ahmed, S., Khan, F., Rusli, R.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.23212 /
Published: Institution of Chemical Engineers 2020
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077430655&doi=10.1016%2fj.psep.2019.12.006&partnerID=40&md5=cee2482fe1be76a644a1297c81db3a96
http://eprints.utp.edu.my/23212/
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spelling utp-eprints.232122021-08-19T05:53:03Z Process Safety Assessment Considering Multivariate Non-linear Dependence Among Process Variables Ghosh, A. Ahmed, S. Khan, F. Rusli, R. Nonlinear dependencies among highly correlated variables of a multifaceted process system pose significant challenges for process safety assessment. The copula function is a flexible statistical tool to capture complex dependencies and interactions among process variables in the causation of process faults. An integration of the copula function with the Bayesian network provides a framework to deal with such complex dependence. This study attempts to compare the performance of the copula-based Bayesian network with that of the traditional Bayesian network in predicting failure of a multivariate time dependent process system. Normal and abnormal process data from a small-scale pilot unit were collected to test and verify performances of failure models. Results from analysis of the collected data establish that the performance of copula-based Bayesian network is robust and superior to the performance of traditional Bayesian network. The structural flexibility, consideration of non-linear dependence among variables, uncertainty and stochastic nature of the process model provide the copula-based Bayesian network distinct advantages. This approach can be further tested and implemented as an online process monitoring and risk management tool. © 2019 Institution of Chemical Engineers Institution of Chemical Engineers 2020 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077430655&doi=10.1016%2fj.psep.2019.12.006&partnerID=40&md5=cee2482fe1be76a644a1297c81db3a96 Ghosh, A. and Ahmed, S. and Khan, F. and Rusli, R. (2020) Process Safety Assessment Considering Multivariate Non-linear Dependence Among Process Variables. Process Safety and Environmental Protection, 135 . pp. 70-80. http://eprints.utp.edu.my/23212/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Nonlinear dependencies among highly correlated variables of a multifaceted process system pose significant challenges for process safety assessment. The copula function is a flexible statistical tool to capture complex dependencies and interactions among process variables in the causation of process faults. An integration of the copula function with the Bayesian network provides a framework to deal with such complex dependence. This study attempts to compare the performance of the copula-based Bayesian network with that of the traditional Bayesian network in predicting failure of a multivariate time dependent process system. Normal and abnormal process data from a small-scale pilot unit were collected to test and verify performances of failure models. Results from analysis of the collected data establish that the performance of copula-based Bayesian network is robust and superior to the performance of traditional Bayesian network. The structural flexibility, consideration of non-linear dependence among variables, uncertainty and stochastic nature of the process model provide the copula-based Bayesian network distinct advantages. This approach can be further tested and implemented as an online process monitoring and risk management tool. © 2019 Institution of Chemical Engineers
format Article
author Ghosh, A.
Ahmed, S.
Khan, F.
Rusli, R.
spellingShingle Ghosh, A.
Ahmed, S.
Khan, F.
Rusli, R.
Process Safety Assessment Considering Multivariate Non-linear Dependence Among Process Variables
author_sort Ghosh, A.
title Process Safety Assessment Considering Multivariate Non-linear Dependence Among Process Variables
title_short Process Safety Assessment Considering Multivariate Non-linear Dependence Among Process Variables
title_full Process Safety Assessment Considering Multivariate Non-linear Dependence Among Process Variables
title_fullStr Process Safety Assessment Considering Multivariate Non-linear Dependence Among Process Variables
title_full_unstemmed Process Safety Assessment Considering Multivariate Non-linear Dependence Among Process Variables
title_sort process safety assessment considering multivariate non-linear dependence among process variables
publisher Institution of Chemical Engineers
publishDate 2020
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077430655&doi=10.1016%2fj.psep.2019.12.006&partnerID=40&md5=cee2482fe1be76a644a1297c81db3a96
http://eprints.utp.edu.my/23212/
_version_ 1741196639469568000
score 11.62408

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