Title: Risk analysis of petroleum transportation using fuzzy rule-based Bayesian reasoning

Authors: Ayman Alghanmi; Zaili Yang; Eduardo Blanco-Davis

Addresses: Logistics, Offshore and Marine Research Institute, Liverpool John Moores University, Liverpool, UK ' Logistics, Offshore and Marine Research Institute, Liverpool John Moores University, Liverpool, UK ' Logistics, Offshore and Marine Research Institute, Liverpool John Moores University, Liverpool, UK

Abstract: Petroleum transportation systems (PTSs) play a critical role in the movement of crude oil from its production sites to end users. Such systems are complex because they often operate in a dynamic environment. Safe operations of the key components in PTSs such as port and shipping are vital for the success of the systems. Risk assessment is a powerful tool to ensure the safe transportation of crude oil. This paper applies a mathematical model to identify and evaluate the operational hazards associated with PTSs, by incorporating a fuzzy rule-based (FRB) method with Bayesian networks (BNs). Its novelty lies in the realisation of risk analysis and prioritisation of the hazards in PTSs when historical failure data is not available. This hybrid model is capable of assisting decision-makers in measuring and improving the PTSs' safety, and dealing with the inherent uncertainties in risk data.

Keywords: Bayesian belief network; BBN; fuzzy set theory; maritime risk; maritime transport; petroleum transportation.

DOI: 10.1504/IJSTL.2020.105854

International Journal of Shipping and Transport Logistics, 2020 Vol.12 No.1/2, pp.39 - 64

Received: 12 Dec 2017
Accepted: 17 Dec 2018

Published online: 10 Mar 2020 *

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