Dynamic and quantitative risk assessment of Cruise ship pod propulsion system failure: An integrated Type-2 Fuzzy-Bayesian approach

Abstract

Azipod propulsion has revolutionized the future of ship propulsion and maneuvering operations with over 20 years of experience, eventually improving ship safety, reliability, energy efficiency, and overall vessel performance. However, it consists of technically complex machinery systems; its breakdown can result in many potential failures with severe repercussions. In this work, an accident-based dynamic risk assessment study of the Cruise ship pod propulsion system has been carried out. It is based on the real-ship accident of the Norwegian Star, which resulted in the loss of ship propulsion. When historical accident statistics are limited, traditional methods fail to address the uncertainty, dynamic environment, and quantitative risk assessment problems. The goals include avoiding worst-case scenarios by illustrating the progression of dynamic change in risk and establishing the Bayesian network framework for dealing with uncertainty more effectively. Interval type-2 Fuzzy expert system is integrated with the dynamic Bayesian network and bow-tie model for quantitative risk assessment, which laid the groundwork for the subsequent hazard identification and quantitative risk assessment. This accident network summarizes how pod machinery operational failures can cause accidents. The estimated sensitive machinery nodes such as Main motor failure, propulsion system, and power system failure are the leading causes of pod propulsion system failures on board cruise vessels. Risk analysts and decision-makers in the marine and offshore engineering industry can use the suggested model as a decision support tool to considerably reduce and eliminate potential failures, improving the ship's safety and system reliability.