Using Multi-agent Simulation to Assess the Future Sustainability of Capability

Abstract

The ability to make sound decisions in an area with many complex interactions, such as the sustainability of future capability, is limited by the tools available to emulate the system under study. Methods used to forecast maintenance capability and capacity to support future systems are typically static and deterministic in nature and hence cannot incorporate the true stochastic nature of maintenance events and the capability changes associated with the “growth” of personnel through their technical mastery journey. By comparison, discrete event simulations provide a dynamic platform within which we can emulate the randomness inherent in complex systems, and the extension to multi-agent simulations allows us to capture the effects of changes attributed to personnel. Using a simulation created to address the question of maintenance sustainability for future capability (Air Traffic Management System) for 44WG as a basis for analysis, this chapter compares the results of a discrete event simulation with no agent-based functionality against models containing successively greater multi-agent functionality. A consistent set of fictitious data was used in the analyses presented to run eight individual scenarios to allow fair comparison. From the analyses, we find the discrete event simulation provides overly optimistic results which would lead to understaffing of the maintenance team. In comparison, the multi-agent simulation results were closer to reality and therefore better suited to inform decision making.