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Adaptable, Automated Troubleshooting Expert

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: FA8501-10-P-0129
Agency Tracking Number: F093-208-0798
Amount: $99,436.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: AF093-208
Solicitation Number: 2009.3
Solicitation Year: 2009
Award Year: 2010
Award Start Date (Proposal Award Date): 2010-07-01
Award End Date (Contract End Date): 2011-03-01
Small Business Information
200 Canal View Blvd
Rochester, NY 14623
United States
DUNS: 073955507
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Patrick Kalgren
 Manager, Electronic Systems PHM
 (585) 424-1990
Business Contact
 Mark Redding
Title: President
Phone: (585) 424-1990
Research Institution

Built-in test, systematic troubleshooting, and tech manuals offer an incremental step towards alleviating troubleshooting complexity, but the ability of system designers to provide meaningful test data and specify optimal troubleshooting at point of design is constrained by necessary development limitations and resources required to execute exhaustive testing and validation of diagnostic strategies. Impact Technologies, in collaboration with the Georgia Institute of Technology, proposes to develop an Adaptable, Automated Troubleshooting Expert decision support tool for the Air Force. The proposed tool leverages existing data sources, from troubleshooting manuals to test and diagnostic data, creating an automated diagnostic expert for advanced troubleshooting assistance and assessment of complex systems. Incorporating maintainer feedback and innovative learning techniques, the tool learns and adapts over time. Much like the grease smudged and dog-eared pages of a good technician’s manual, the learning algorithm captures knowledge and preserves and extends its utility for broader use. Much like a “learned expert” or “esteemed colleague,” the intelligent, expert diagnostic support system provides a time and cost saving resource for maintenance and support of Air Force systems ranging from mechanical to electrical and electronic. The proposed modular software architecture and standards-based, open, interfaces support adaptability and reusability across multiple application domains. BENEFIT: The intelligent diagnostic decision support tool offers reduced overhead associated with long troubleshooting times for failures in complex systems, along with a potential reduction in required technical expertise and manpower. Automated learning and encapsulation of institutional knowledge extends the utility of local expertise. Commercial applications include transportation, medical, manufacturing, and utility domains. Complex systems must be maintained and the technology boom has created increasingly complex systems and a need for this technology.

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

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