Impact Technologies developed a model-based decision support Framework that facilitates the use and development of decision support tools in a CBM environment. The Framework leverages existing CBM and PHM data to provide enhanced automated strategic analysis. Its modular structure promotes reusability of components to expedite development of new decision capabilities, making it extensible to many different operational environments. The Framework also embraces open architecture and standardized data interfaces for increased supportability and upgradeability. An advanced probability-based mission readiness forecasting and assessment tool developed by Impact Technologies for the U.S. Navy was used to illustrate how the proposed Framework facilitates the assembly of independent decision support tools to provide a high fidelity knowledge product. In this application the Framework combined three separate functional areas — a mission profile modeling tool, a system relational model, and a maintenance optimization module. The mission profile modeling tool provided the ability to create functional representations of multi-layered complex systems for any mode of operation, accounting for different machinery line-ups, redundancy, system-to-system interactions, and component and sub-system criticalities. The system relational model provided the overall system probability of failure calculated based on the current and projected system configuration and usage. The maintenance optimization module determined the safest and most cost-effective time to perform required and opportunistic maintenance. The resulting software product enables the comparison of multiple what-if scenarios where the scheduling of maintenance and logistics support activities can be optimized based on resource availability and the propagation effects of those actions can be measured in terms of readiness at any level within the system hierarchy. A visual assessment of the ship’s probability of completing the prescribed mission of any combination of ship operations (e.g., anti-surface warfare, non-combat operations, or mine warfare) can be generated so corrective actions in the form of maintenance or changes to mission operations can be evaluated. The tool incorporates several novel approaches including fusion of multiple independent low-level indicators to predict overall system readiness, methodologies to account for the interactive effects of interconnected subsystems, and a risk-based optimization to select and schedule the optimal maintenance schedule. This paper summarizes the features of the model-based decision support tool Framework and the mission readiness software application developed using this architecture.

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