Framework for post-prognostic decision support

IEEE Aerospace Conference Proceedings

Volumn 2006, Issue , 2006, Pages

  Iyer, Naresh ^a   Goebel, Kai ^a   Bonissone, Piero ^a  

^a GE GLOBAL RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION SOURCES; OPERATIONAL DECISION MAKING; POST-PROGNOSTIC DECISION SUPPORT; PROGNOSTICS AND HEALTH MANAGEMENT (PHM) SYSTEMS;

AVIONICS; CONDITION MONITORING; DECISION MAKING; INFORMATION SYSTEMS; MAINTENANCE;

DECISION SUPPORT SYSTEMS;

EID: 34047161106     PISSN: 1095323X     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

1. P. Bonissone and K. Goebel, "When will it break? A Hybrid Soft Computing Model to Predict Time-to-break Margins in Paper Machines", Proceedings of SPIE 47th Annual Meeting, International Symposium on Optical Science and Technology, Vol. #4787, pp. 53-64, 2002.
2. A. Garga, K. McClintic, R. Campbell, C.-C. Yang; M. Lebold, T. Hay, C. Byington, "Hybrid Reasoning for Prognostic Learning in CBM Systems", IEEE Proceedings Aerospace Conference, vol. 6, 10-17 March 2001, pp. 2957-2969, 2001.
3. K. Goebel, P. Bonanni, N. Eklund, "Towards an Integrated Reasoner for Bearings Prognostic", Proceedings of 2005 IEEE Aerospace Conference, paper z11_0704, 2005.
4. J. Horn, Multicriteria decision making and evolutionary computation. In: Back T, Fogel DB, Michalewicz Z, editors. Handbook of evolutionary computation. Bristol, UK: Institute of Physics Publishing; 1997.
5. Iyer N.S., Aragones, J. K., Hansen, C. H. (2002a). An Event-Driven Monte-Carlo Simulation for Engine Service Planning. Class 2 Technical Report, GE GRC, Service Algorithms Lab (Information and Decision Technologies Group).
6. Iyer N.S., Aragones, J. K., Hansen, C. H. (2002b). An Event-Driven Monte-Carlo Simulation for Engine Service Planning: A Design Description Document. Class 3 Technical Report, GE GRC, Service Algorithms Lab (Information and Decision Technologies Group).
7. th National Conference of the American Association for Artificial Intelligence, Madison, Wisconsin, pp. 143-150, 1998.
8. J. Littles and M. Buczek, "Engine System Prognosis", Proceedings of Materials Science & Technology 2004, September 26-29, 2004, New Orleans, Louisiana, 2004.
9. A. Tversky (1969). Intransitivity of preferences. Psychological Review, 76(1), pp 31-48.
10. G. Vachtsevanos, P. Wang, :Fault Prognosis Using Dynamic Wavelet Neural Networks", AUTOTESTCON Proceedings, IEEE Systems Readiness Technology Conference, 20-23 Aug. 2001, pp. 857-870, 2001.
11. R. Xu, M. Stevenson, C.-M. Kwan, and L. Haynes. "Bearing Monitoring", Proceedings of SPIE - Component and Systems Diagnostics, Prognosis, and Health Management, P. Willett, T. Kirubarajan, (Eds), vol. 4389, pp. 216-218, July 2001.