Prognostics and Health Management (PHM) for Afloat Information Technology (IT) and Network Services

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00039-07-C-0100
Agency Tracking Number: N071-108-1254
Amount: $99,488.00
Phase: Phase I
Program: SBIR
Awards Year: 2007
Solicitation Year: 2007
Solicitation Topic Code: N07-108
Solicitation Number: 2007.1
Small Business Information
100 Great Meadow Rd., Suite 603, Wethersfield, CT, 06109
DUNS: 808837496
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Sudipto Ghoshal
 Manager, Professional Services
 (860) 257-8014
 sudipto@teamqsi.com
Business Contact
 Chakrapani Vallurupalli
Title: President & Chief Operating Officer
Phone: (860) 257-8014
Email: chuckv@teamqsi.com
Research Institution
N/A
Abstract
Qualtech Systems, Inc., in cooperation with University of Connecticut and Lockheed Martin Corporation, propose to develop an integrated on-line and adaptive remote network PHM solution to address the needs of shipboard IT/Network systems and services. The team proposes a network system model suitable for fault localization, which takes into account the fault-to-failure progressions among the different components and/or subsystems. We also propose advanced prognostic techniques to predict discrete events (e.g., router failures), as well as continuous network performance measures (e.g., response time, throughput). The proposed solution performs smart tests (e.g., network probing, database query) on network components and coordinates multiple subsystem health assessments to arrive at an overall network health assessment. For further fault isolation, the solution provides adaptive guided troubleshooting support for the maintenance personnel onboard or onshore. In addition, the solution provides various prediction algorithms tailored to the task of projecting the future network health status for improved Maintenance and Material Management. The work proposed here seeks to developing methods for improved diagnostic accuracy (i.e., root-cause isolation), online implementation (efficient test sequences, fast inferencing), as well as the capability for Remote Diagnostics which provide opportunities to conduct diagnostics remotely and prevent breakdowns by detecting and isolating faults earlier.

* Information listed above is at the time of submission. *

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