An extended Monte Carlo method on simulating the development cost uncertainties of aircraft

Monte Carlo Simulation is a general method for evaluating a deterministic model by iteratively generating inputs so as to get the natural distribution of outputs, which has often been employed for risk analysis of development cost estimation under uncertain environment. However, the traditional way of implementing Monte Carlo Simulation on cost risk analysis is always based on deterministic Cost Estimation Relation (CER) model and does not take the uncertainty of history cost data used to build CER into account, which will considerably affect the cost risk analysis. In this paper, we extend Monte Carlo Simulation model to make its simulating process cover the stage of building model so that not only the inputs are iteratively generated but also the model is iteratively rebuilt. An example is carried out to compare the extended model to the traditional one on analyzing aircraft development cost risk, which shows that the risk distribution gotten by Extended Monte Carlo Simulation is considerably different to that gotten by traditional one.