Combining various facets of uncertainty in whole-life cost modelling

Estimates for various parameters in a whole-life costing (WLC) exercise are obtained from different sources each with its own level and type of uncertainty. A practical procedure is developed to handle statistically significant data and expert assessments within the same whole-life costing (WLC) model calculation. First, various methods used to combine random and subjective data are critically reviewed with emphasis on their suitability to WLC modelling. This is followed by the identification of an appropriate mathematical framework into which all information and data are transformed to a common representation making their integration a straightforward task. The proposed procedure is then implemented into a computational algorithm. The efficacy of the algorithm is explained in the context of a selected example application.