TY  - JOUR
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077430655&doi=10.1016%2fj.psep.2019.12.006&partnerID=40&md5=cee2482fe1be76a644a1297c81db3a96
A1  - Ghosh, A.
A1  - Ahmed, S.
A1  - Khan, F.
A1  - Rusli, R.
JF  - Process Safety and Environmental Protection
VL  - 135
Y1  - 2020///
N2  - 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
KW  - Bayesian networks; Process monitoring; Risk management; Safety engineering; Statistical mechanics; Stochastic models; Stochastic systems
KW  -  Copula functions; Multivariate process; Nonlinear dependencies; On-line process monitoring; Process safety; Stochastic nature; Structural flexibilities; Time-dependent process
KW  -  Complex networks
ID  - scholars13416
EP  - 80
SN  - 09575820
PB  - Institution of Chemical Engineers
N1  - cited By 20
TI  - Process Safety Assessment Considering Multivariate Non-linear Dependence Among Process Variables
SP  - 70
AV  - none
ER  -