Instead of performing maintenance at fixed intervals, the operational efficiency of assets can be improved significantly by taking into account the variations in usage and operating environment of the asset. In that way, the traditional static maintenance policy is replaced by a dynamic maintenance policy. In the present work, this concept is demonstrated by modeling the failure behavior of a rather complex multi-component system, i.e. a navy frigate. For this system, several non-identical subsystems are included. Some of the systems are unique on board, while others have been made redundant, which means that the criticality of the subsystems to the mission capability of the frigate varies. Moreover, the variation in deployment of the frigate in terms of mission types and operating environments is translated into various usage profiles for the subsystems. Simulations are then performed to obtain the optimal maintenance policy in terms of interval length and preventive maintenance threshold, given certain requirements for the deployability of the frigate in a certain period. Moreover, the sensitivity of the results for different subsystem initial service life times and variations in usage profile are investigated. The results show a clear dependence of the optimal interval on the mission program of the frigate and the subsystem failure behavior.

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In modeling military (inter)actions and cooperation as networks, military units or actors may be represented as nodes. In analyzing military networked action, a key observation is that a node is not just part of one type of network but simultaneously belongs to multiple networks. To model the dynamical behavior of actors, one has to take into account the interdependence of the different networks. In this chapter, the authors present a method that is used to implement, analyze, and evaluate some specific principles that may be used by the actors in an organization to drive the process of constant change. It can be used to analyze the effect of these principles on the metrics for coordination, synchronization, robustness, and desired operational effectiveness of the network as a whole. To demonstrate the approach, the authors apply it to networks in which two basic principles are operational: reciprocity and a novel principle called covering.

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