The developed model relies upon the generation of random variables from input probability distributions and these are represented in the model equations by the name of the probability distribution (e.g. Poisson, triangular etc.) followed by the parameters in brackets. The model used Monte Carlo simulation techniques (Vose, 2000) to create the output distributions. Monte Carlo methods repeatedly select values randomly from distributions to create multiple scenarios of a problem. Together, these scenarios give a range of possible solutions, some of which are more probable and some less probable, resulting in a probability distribution for the solution parameter.