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You are here: Home » Case Studies » Minimising whole-life costs of vehicle fleets
Minimising whole-life costs of vehicle fleets
Problem
- A client (QinetiQ) is responsible for helping the MOD
decide on alternative designs for new vehicles that have to meet a
particular operational requirement
- The choice is between adopting a particular vehicle with or without a new class of technology
- The decision on which alternative to adopt must take account
of the whole-life fleet cost. Thus, for example, adopting the new fleet
with the new technology may involve much higher up-front development
and unit costs, but over its life-time greater reliability and
maintainability may require fewer vehicles to meet the operational
requirement. Hence the whole life-costs could be lower
- There was previously no method for a) dealing with the
mixture of objective and subjective data required to solve this problem
and b) quantifying the inevitable uncertainty
Solution
- A model was built in AgenaRisk that incorporated all
the factors impacting on repair efficiency and reliability as well as
the whole-life cost factors
- To run the model users simply input the operational
requirements (the number of vehicles that have to be available at the
end of a combat operation) together with the features that characterize
the different alternative designs. AgenaRisk then calculates (for each
alternative) the number of vehicles that need to be bought and the
total whole-life costs
- The results for the two alternative are plotted against each other
- The unique simulation capability in AgenaRisk was used to
full effect: numeric variables were created without any need to create
artificial discretisations, and this also ensured highly accurate
results
- The model incorporates periods of peacetime and wartime missions
Benefits
- AgenaRisk provides a rigorous, auditable prediction
of the relative whole life costs and hence provides a clear basis for
making the critical decision
- AgenaRisk enables extensive "what-if?" and other types of
sensitivity analysis to enable users to identify the impact of changes
to different factors and assumptions
- AgenaRisk identifies the causes of increased cost and poorer quality
