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Automated System (H/W & S/W) Test and Repair Tool

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00024-10-C-4120
Agency Tracking Number: N082-184-0610
Amount: $593,809.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: N08-184
Solicitation Number: 2008.2
Timeline
Solicitation Year: 2008
Award Year: 2010
Award Start Date (Proposal Award Date): 2009-10-26
Award End Date (Contract End Date): 2011-10-25
Small Business Information
727 Airport Boulevard
Ann Arbor, MI 48108
United States
DUNS: 197187602
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: Yes
Principal Investigator
 Chris Lomont
 Research Engineer
 (734) 668-2567
 proposals@cybernet.com
Business Contact
 Charles Jacobus
Title: President
Phone: (734) 668-2567
Email: proposals@cybernet.com
Research Institution
N/A
Abstract

The growing complexity of distributed submarine combat systems has limited the Navy''s capability to test and repair software and hardware under a wide range of fault scenarios. The rapid deployment of networked systems has not yet led to an equally advanced plan for the maintenance community to identify and perform preventative maintenance on these systems. As a result, the potential for mission failure due to system faults has risen to an unsatisfactory level. To address this problem, Cybernet developed the architecture for an Automated System Test and Repair System (A-STAR) that will detect system faults and automate repair actions with minimal input from a Crew Member. A-STAR will reduce the time required to verify and maintain the integrity of today''s submarine combat system, and minimize the possibility of system failure during mission critical operations by continuously monitoring the integrity of the Submarine CCS for faults and providing Navy crew members the solutions in real time. Ultimately, A-STAR will deliver the Navy the following capabilities: Detection and alert of combat control system faults; generation of repair actions for resolving mission critical functions; generation of system design metrics based on the accumulated knowledge base; and automated execution of predictive repair actions.

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

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