Dynamic behavioural model for assessing impact of regeneration actions on system availability: Application to weapon systems

Mastering system availability all along the system life cycle is now a critical issue with regards to systems engineering. It is more true for military systems which operate in a battle context. Indeed as they must act in a hostile environment, they can become unavailable due to failures of or damage to the system. In both cases, system regeneration is required to restore its availability. Many approaches based on system modelling have been developed to assess availability. However, very few of them take battlefield damage into account and relevant methods for the model development are missing. In this paper, a modelling method for architecture of weapon system of systems that supports regeneration engineering is proposed. On the one hand, this method relies on a unified failure/damage approach to extend acknowledged availability models. It allows to integrate failures, damages, as well as the possibility of regeneration, into operational availability assessment. Architectures are modelled as a set of operational functions, supported by components that belong to platform (system). Modelling atoms (i.e. elementary units of modelling) for both the architecture components and functions are defined, based on state-space formalism. Monte Carlo method is used to estimate availability through simulation. Availability of the architecture is defined on the basis of the possible states of the required functions for a mission. The states of a function directly depend on the state of the corresponding components (i.e. the components that support the function). Aggregation rules define the state of the function knowing the states of each component. Aggregation is defined by means of combinatorial equations of the component states. The modelling approach is supported by means of stochastic activity network for the models simulation. Results are analysed in terms of graphs of availability for mission's days. Thus, given the simulation results, it is possible to plan combat missions based on criteria such as the number of platforms to be involved given functions required for the mission or the mean of regeneration to be deployed given the possible threats. Further, the simulation will help towards the design of improved architecture of system of systems which could focus on the factors affecting the availability.