Title :
Evidence-based Bayesian networks approach to airplane maintenance
Author :
Kipersztok, Oscar ; Dildy, Glenn A.
Author_Institution :
Math. & Comput. Technol., Boeing Co., Seattle, WA, USA
fDate :
6/24/1905 12:00:00 AM
Abstract :
A system that facilitates airplane maintenance provides decision support for finding the root-cause of a failure from observed symptoms and findings. Such system provides diagnostic advice listing the most probable causes and recommending possible remedial actions. Furthermore, its goal is to reduce the number of delays and cancellations and unnecessary parts removal, which add significant costs to airplane maintenance operations. A Bayesian belief network, model-based approach is presently being used for building such diagnostic models. The paper describes the pertinent issues in using such models
Keywords :
aerospace computing; aircraft maintenance; belief networks; case-based reasoning; decision support systems; diagnostic expert systems; neural nets; DSS; airplane maintenance; decision support system; diagnostic advice; evidence-based Bayesian networks; failure cause finding; remedial actions; root-cause; Air safety; Airplanes; Bayesian methods; Computational modeling; Computers; Costs; Delay; Maintenance; Mathematics; Medical simulation;
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7278-6
DOI :
10.1109/IJCNN.2002.1007607