Data collection and analysis for remote networks

System monitors and determines useful life of components, failure modes, and maintenance actions to remedy or avoid an incident

Software & Information Technology

This cruise ship contains hundreds of components that need health monitoring both on-board and at a central data analysis center.

Expanding corporate and federal data networks makes information system analysis ever more complex. Such growth is compromising the ability to assess system readiness and component lifecycles. As networks expand beyond the walls of a building to remote or mobile locations, this complexity dramatically increases.

Today the data collection and analysis process is often manual and usually tedious. In the context of the distributed and siloed information systems, each system has its own method of collecting data, and synchronizing disparate systems is difficult. Large-scale continuous data collection is rare due to its human capital requirements and bandwidth constraints of computing networks. Some legacy systems lack the built-in-tests and prognostics requirements so implementation for health monitoring is difficult. Another challenge with data analysis is the ability to relate various data sets into productive recommendations for future system improvements and device maintenance. While a lot of system data has been slowly gathered throughout the years, there have not been adequate studies to evaluate the correlation between the different data types. The outcome is that a majority of the recommendations are still greatly influenced by the interest and experience of the subject matter expert, without sufficient quantitative data to support or legitimize the result. Further, most data collection and data analysis capabilities do not integrate directly into the operations support team and its remote support capability, delaying support responses that could otherwise mitigate impending issues effectively.

The Navy is addressing the above with an operations network for data collection and analysis. The system uses sensor data indicating system health, detected fault codes, and performance parameters associated with one or more system elements of the network. This approach can identify system degrading trends and collect and track reliability metrics (system performance data). A central data hub processes the received performance data into remaining useful life and other prognostics health management information and provides the information to technicians.

The Navy’s embodiment of the above approach is the Secure Shipboard Information Management System, which is currently being tested aboard destroyers. The near-term goal is to equip the entire surface fleet with the ability to transmit data to shore systems for maintenance analysis and in-service engineering agents (ISEA) development.

In the private sector, the network could be implemented within a cruise ship or offshore drilling platform. In this example, the system provides a network domain that can represent navigation systems and weather radar systems deployed on cruise ships or drilling platforms. In such applications, maintenance data is collected, stored and analyzed to discern current and prospective system failures as well as provide corrective actions to address these failures.

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