An advanced risk analysis approach for container port safety evaluation

Article English OPEN
Alyami, H ; Lee, PT-W ; Yang, Z ; Riahi, R ; Bonsall, S ; Wang, J

Risk analysis in seaports plays an increasingly important role in ensuring port operation reliability, maritime transportation safety and supply chain distribution resilience. However, the task is not straightforward given the challenges, including that port safety is affected by multiple factors related to design, installation, operation and maintenance and that traditional risk assessment methods such as quantitative risk analysis cannot sufficiently address uncertainty in failure data. This paper develops an advanced Failure Mode and Effects Analysis (FMEA) approach through incorporating Fuzzy Rule-Based Bayesian Networks (FRBN) to evaluate the criticality of the hazardous events (HEs) in a container terminal. The rational use of the Degrees of Belief (DoB) in a fuzzy rule base (FRB) facilitates the implementation of the new method in Container Terminal Risk Evaluation (CTRE) in practice. Compared to conventional FMEA methods, the new approach integrates FRB and BN in a complementary manner, in which the former provides a realistic and flexible way to describe input failure information while the latter allows easy updating of risk estimation results and facilitates real-time safety evaluation and dynamic risk-based decision support in container terminals. The proposed approach can also be tailored for wider application in other engineering and management systems, especially when instant risk ranking is required by the stakeholders to measure, predict and improve their system safety and reliability performance.
  • References (7)

    1. AL YAMI H., YANG Z., RAMIN R. BONSALL S. and WANG J. (2013), “A new risk analysis approach for container terminal safety evaluation.” International Conference on Challenges and Responses of Ports in A Globalised Economy, April 3-5, Bangkok, Thailand.

    2. ANDERSEN, S., OLESEN, K.G., JENSEN, F.V. & JENSEN, F. 1990. “HUGIN - a shell for building Bayesian belief universes for expert systems.” In: Reading in Uncertainty, G. Shafer, and J. Pearl, (eds.), San Francisco: Morgan Kaufmann Publishers, 332-337.

    3. BRAGLIA, M., FROSOLINI, M. & MONTANARI, R. 2003. “Fuzzy criticality assessment model for failure modes and effects analysis.” International Journal of Quality & Reliability Management, 20: 503-524.

    44. YANG Z., NG, A.K.Y. & WANG, J. 2014. “A new risk quantification approach in port facility security assessment.” Transportation Research Part A: Policy and Practice,59: 72-90.

    45. YANG, Z., WANG, J., BONSALL, S. & FANG, Q. 2009. “Use of Fuzzy Evidential Reasoning in Maritime Security Assessment.” Risk Analysis, 29(1): 95-120.

    46. YI, D., KIM, S. CHOI, H., PARK, N. & LEE, T. 2000. “Developing a conceptual model for sharing container terminal resources: a case study of the Gamman container terminal.” Maritime Policy &Management, 27(2): 155-167.

    47. ZADEH, L.A. 1965. “Fuzzy sets.” Information and Control, 8(3): 338-353.

  • Metrics
    views in OpenAIRE
    views in local repository
    downloads in local repository

    The information is available from the following content providers:

    From Number Of Views Number Of Downloads
    LJMU Research Online - IRUS-UK 0 399
Share - Bookmark