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Cited by 156Risk and Safety AnalysisMaritime Ports and LogisticsMaritime Navigation and Safety

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Advanced uncertainty modelling for container port risk analysis

Open access
Alyami, Hani, Yang, Zaili, Riahi, Ramin, Bonsall, Stephen, Wang, Jin·2019·Accident Analysis & Prevention
DOI 10.1016/j.aap.2016.08.007
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Abstract

Globalization has led to a rapid increase of container movements in seaports. Risks in seaports need to be appropriately addressed to ensure economic wealth, operational efficiency, and personnel safety. As a result, the safety performance of a Container Terminal Operational System (CTOS) plays a growing role in improving the efficiency of international trade. This paper proposes a novel method to facilitate the application of Failure Mode and Effects Analysis (FMEA) in assessing the safety performance of CTOS. The new approach is developed through incorporating a Fuzzy Rule-Based Bayesian Network (FRBN) with Evidential Reasoning (ER) in a complementary manner. The former provides a realistic and flexible method to describe input failure information for risk estimates of individual hazardous events (HEs) at the bottom level of a risk analysis hierarchy. The latter is used to aggregate HEs safety estimates collectively, allowing dynamic risk-based decision support in CTOS from a systematic perspective. The novel feature of the proposed method, compared to those in traditional port risk analysis lies in a dynamic model capable of dealing with continually changing operational conditions in ports. More importantly, a new sensitivity analysis method is developed and carried out to rank the HEs by taking into account their specific risk estimations (locally) and their Risk Influence (RI) to a port's safety system (globally). Due to its generality, the new approach can be tailored for a wide range of applications in different safety and reliability engineering and management systems, particularly when real time risk ranking is required to measure, predict, and improve the associated system safety performance.

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  • When lacking historical failure data, the three FMEA parameters are often defined by linguistic terms to better describe and model subjective assessments.

    “When lacking historical failure data, the three parameters are often defined by linguistic terms in order to better describe and model subjective assessments (Yang et al., 2008;Alyami et al., 2019).”

    From A BN driven FMEA approach to assess maritime cybersecurity risks (2023) · cites this paper as Alyami et al., 2019

    The Introduction links missing or uncertain failure data to uncertainty-modelling methods, and the Literature review identifies three traditional FMEA attributes. The sensitivity-analysis section says linguistic variables describe risk parameters, but the paper’s container-port model uses four parameters rather than establishing that the three traditional attributes are often defined in linguistic terms when historical data are lacking. No page numbers are available in our copy. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

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Metadata

Authors
Alyami, H., Yang, Z., Riahi, R., Bonsall, S., & Wang, J.
Affiliations
Liverpool John Moores University (GB)
Corresponding author
Yang, Zaili
ORCID
Venue
Accident Analysis & Prevention
Publisher
Elsevier BV
Published
2019-02
Volume
123
Pages
411-421
ISSN
0001-4575 (ISSN-L)
DOI
10.1016/j.aap.2016.08.007
OpenAlex
W2512403973
Cited by
156
References
0
Citations by year
2026: 19 · 2025: 26 · 2024: 22 · 2023: 26 · 2022: 18 · 2021: 12 · 2020: 19 · 2019: 3
FWCI
7.60
Type
journal article
Language
en
Open access
Licence
Locations
  • Accident Analysis & Prevention (publishedVersion)
  • PubMed (publishedVersion)
  • Liverpool John Moores University (submittedVersion)
Funders
  • Faculty of Engineering and Technology at Liverpool John Moores University, UK
  • King Abdul-Aziz University, KSA
Topics
  • Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Risk and Safety Analysis
  • Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Maritime Ports and Logistics
  • Physical Sciences › Engineering › Ocean Engineering › Maritime Navigation and Safety
Keywords
safety performance evaluation, failure mode and effects analysis, evidential reasoning, uncertainty modeling, hazardous events, risk prioritization, sensitivity analysis, risk-based decision support, port safety
MeSH terms
Bayes Theorem, Commerce, Humans, Ships, Reproducibility of Results, Risk Assessment, Uncertainty, Internationality

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