Real-time Data Collection, Trending and Analysis for Surface Ship Diesel Engine Operations and Maintenance Optimization

Marine Diesel Engine Systems require a process for automating the collection and analysis of system specific data associated with fleet-wide operational performance. The purpose of implementing such a process is to leverage the benefits of executing appropriate Lifecycle Maintenance (LCM) Requirements, recommending Condition Based Maintenance (CBM) when applicable and predicting risks that could lead to catastrophic failures early enough to mitigate the risks to these vital systems. This process should be an integration of elements, which automatically collects real-time Reliability, Maintainability, and Availability (RMA) data, conducts diagnostic/prognostic analysis, and provides actionable recommendations, reports and access to users throughout the community. Analysis will include total and sub-system diesel engine health assessment and prediction, trending of input and output data and other selected maintenance related functions. Leveraging the automated data collection, centralized repository, and analysis system for Towed-Array System (TAS) RMA related data LCE developed in the PHASE I Topic N00-048, LCE now proposes to extend these concepts and processes to the more complex main propulsion and electrical generation systemsÆ diesel engines. This effort builds upon previously demonstrated monitoring of less complex individual ship system health. The database will be integrated with both new and existing design and modeling simulation tools, enabling the prediction of the health of the entire FleetÆs diesel engines. The combination of this technology and processes with existing Diesel Engine Program analytical processes will provide the basis for the implementation of an integrated predictive tool with diagnostic process technology.