Decision making based on the value of information of different inspection methods

Decision makers face several challenges in the aftermath of a disastrous event. Emergency operations such as traffic restrictions, bridge closures and immediate repairs might have to be scheduled in order to keep an appropriate level of safety. The state of the infrastructure after the occurrence of the seismic event can be predicted based on the a priori knowledge about the system, and decisions may be taken based on this knowledge. This is generally done by minimizing the expected cost of the different plans of action, considering both direct (e.g. failure of a component) and indirect costs (e.g. costs coming from diverted traffic after a bridge closure). However, inspections of selected critical components can provide insight into the actual state of the system and consequently change the chosen plan of action for the decision makers. Different methods of inspections come at different costs, information and uncertainties. It is important to decide whether or not inspections should be done and if so select the most appropriate inspection method so that the associated costs do not overcome the benefits that would be obtained by performing it. Moreover, advanced monitoring techniques that are able to investigate the state of the system over time (such as sensor monitoring) can provide additional information about the way the system is evolving. This information can in turn be used to update the knowledge about the state of the system before the occurrence of a disastrous event, further reducing the chance of taking the wrong managing decision. Before installation, decision makers must properly evaluate the costs associated to these monitoring techniques, to decide whether the additional information overcomes their cost. In this work, we propose a general framework to evaluate the Value of Information of selected inspection procedures considering the possible information from structural health monitoring (SHM) of system. The proposed framework will be applied to a case study of a two-span reinforced concrete bridge.