Jan 1, 1997
In the spring of 1994, the Office of the Secretary of Defense was coordinating the Airlift Requirements Study, in which a simulation model developed by the Air Force was to be used to analyze alternative fleets of passenger and cargo aircraft. However, certain model inputs had been criticized, especially in the earlier C-17 Cost and Effectiveness Analysis, for contributing to model-generated estimates of airlift capacity that were "too optimistic" and for "overestimating" the ability of the airlift system to move forces and supplies into overseas theaters of operation. The desire for more-realistic inputs describing airfield capacities led to the first RAND study, which produced an initial version of the Airfield Capacity Estimator (ACE). This report describes follow-on work to investigate how differing levels and distributions of airfield resources, over a set of airfields, can affect airlift throughput. That work resulted in substantial improvements to the ACE model. The report documents the logic, implementation, and initial applications of this revised version of ACE. The report recommends that planners and others interested in airlift flow through airfields of various types and locations no longer use standard minimum times on ground (MOGs) or standard ground times but, instead, estimate the specific aircraft ground time and airfield capacity for each stopover by carefully considering the servicing, fueling, and loading operations needed for each type of mission stopping at each airfield, and the major ground resources available at each airfield. It also recommends that the mobility community now focus its research efforts on detailing realistic availability times for the commonly used pieces of material-handling equipment and on updating and validating its estimated distributions for aircraft repair times. This report should be of interest to deployment planners, and to air mobility resource programmers and managers.
Conclusions and Recommendations
Details of the Approach
Tips for Using Ace
Screens and Data