Diagnosis-Driven Prognosis for Decision Making

Award Information
Agency: National Aeronautics and Space Administration
Branch: N/A
Contract: NNX15CA11C
Agency Tracking Number: 144546
Amount: $749,999.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: A1.04
Solicitation Number: N/A
Timeline
Solicitation Year: 2014
Award Year: 2015
Award Start Date (Proposal Award Date): 2015-05-18
Award End Date (Contract End Date): 2017-05-17
Small Business Information
99 East River Drive, East Hartford, CT, 06108-7301
DUNS: 808837496
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Somnath Deb
 President, CTO
 (860) 761-9344
 deb@teamqsi.com
Business Contact
 Sudipto Ghoshal
Title: Business Official
Phone: (860) 761-9341
Email: sudipto@teamqsi.com
Research Institution
N/A
Abstract
In Phase II, the QSI-Vanderbilt team seeks to develop a system-level diagnostics and prognostic process that incorporates a "sense and respond capability," which first uses error codes and discrete sensor values to correctly diagnose the system health including degradations and failures of sensors and components, and then invokes appropriate prognostics routines for the assessment of RUL and performance capability. The QSI-Vanderbilt team plans to emphasize advancement in the following five areas: (a) leverage extensive LADEE telemetry data to further enhance and develop online degradation profiles, performance analysis and remaining useful life (RUL) computation algorithms, (b) develop/implement degradation detection algorithms to compute time-to-alarm (TTA) and time-to-maintenance (TTM) predictions and correlate with alarm/maintenance events, (c) develop reusable library of models and tests, (d) verification and validation of the resulting solution, and (e) demonstrate the proposed solution on LADEE's and other spacecraft subsystems. Once fully developed, outcomes of this effort will lower the cost of developing prognostics and provide maximum critical system availability, smarter scheduling of maintenance, overall logistics support cost, and optimal match of assets to missions. The proposed offering will also provide a cost-effective and pragmatic solution to our commercial customers who want to reduce unscheduled downtime by practicing condition based maintenance, but cannot justify the cost of developing prognostic methods in the conventional way.

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

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