Statistical Simulation of Life Cycle Cost

This paper contributes to literature aiming to improve corporate decision-making policies in times of depressed margins and increased business uncertainty. Starting from a case study based on actual servicing systems, it develops and applies a value-based decision-making model using a combination of life cycle costing and statistical simulation. It is shown that this approach generates meaningful results wherever there are alternative solutions available for component parts of servicing units, differing in a range of functional characteristics and involving risk. In contrast to conventional capital budgeting, such a model provides full assessment of contingent or intangible costs, such as the impacts of device reliability. Simulation results and their reliability can be analyzed using standard statistical methods. Sensitivity analyses are vital for the determination of relevant risk factors.