Chapter 10 Three novel risk modelling and decision making techniques

This Chapter presents three novel safety assessment and decision making approaches. They are (1) a safety based decision support system using artificial neural network techniques, (2) a safety optimisation framework using Taguchi concepts, and (3) a multiple criteria decision approach applied to safety and cost synthesis. Such approaches provide the safety analyst with more flexibility and may be more appropriate in situations where satisfactory results cannot be obtained using other methods. A risk estimation framework incorporating artificial neural networks (ANNs) is described with two case studies demonstrating its use. Some suggestions are made for further research and development on ANN techniques in the context of maritime safety assessment. The possibility to pool records on notation fields such as system data, function information and casualty or defect data in an agreed and standardised database structure is discussed. A safety optimisation framework using the Taguchi concepts is described with an example demonstrating its use. The Taguchi concepts are described and discussed. Orthogonal arrays are used to study multiple parameters simultaneously with a minimum of time and resources to produce an overall picture for more detailed safety based design and operational decision making. The signal-to-noise ratio is employed to measure quality, in this case, risk level. The outcomes produced using the described framework may provide the fundamental knowledge for safety analysts to make safety based design and operation decisions. A new safety and cost modelling approach is described and demonstrated by an example. Three typical multiple criteria decision analysis methods for safety and cost synthesis are described. Their potential for use in safety base decision making is discussed. © 2003 Elsevier B.V. All rights reserved.