(Georgia Institute of Technology, 2012-07-26)
Dees, Patrick Daniel
During development of a complex system, feasibility initially overshadows other concerns, in some cases leading to a design which may not be viable long-term. In particular for the case of Reusable Launch Vehicles, Operations&Maintenance comprises the majority of the vehicle's LCC, whose stochastic nature precludes direct analysis. Through the use of simulation, probabilistic methods can however provide estimates on the economic behavior of such a system as it evolves over time. Here the problem of operations optimization is examined through the use of discrete event simulation. The resulting tool built from the lessons learned in the literature review simulates a RLV or fleet of vehicles undergoing maintenance and the maintenance sites it/they visit as the campaign evolves over a period of time. The goal of this work is to develop a method for uncovering an optimal operations scheme by investigating the effect of maintenance technician skillset distributions on important metrics such as the achievable annual flight rate and maintenance man hours spent on each vehicle per flight. Using these metrics, the availability of technicians for each subsystem is optimized to levels which produce the greatest revenue from flights and minimum expenditure from maintenance.