Missile Maintenance Management Using Data Flow Analysis and Discrete Event Simulation

The data flow analysis and the discrete event simulation are utilized to assist the decision making of missile maintenance management. In contrast to the traditional qualitative methods, first the association and the similarity analyses are used to mine the inner relationship between the real-time data flow and the historical data flow. The Apriori algorithm and the Dynamic Time Warping (DTW) algorithm are utilized to help the user to detect the abnormity of the equipment maintenance data flow and evaluate the working performance of the project group. Second, the discrete event simulation technique is employed to model the process of stochastic event of the missile maintenance management. As a result, the user can understand, analyze, and monitor the event change state of the whole maintenance process. And the user can also decide how to allot the limited resource to different project groups scientifically. Some experimental results have proved the validity and effectiveness of proposed methods.