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Integration of damage stability into a risk management framework

The multi-dimensional character of ship safety requires a framework where holistic risk management can be performed efficiently and cost-effectively. In this respect, the links between safety performance indicators and ship life-cycle attributes (ship parameters, operational characteristics, etc.) should be established probabilistically in order to capture the inherent variations of this process and account for the evident diversity. In light of this situation, a data mining framework for ship safety management is presented in this paper. The approach builds on Bayesian Networks, as a risk modelling technique, and on the systematic extraction of information stored in available data. Particular emphasis is placed on the integration of aspects of damage stability into such a framework for an overall management of ship lifecycle safety.