@inproceedings{2733e04568864c1daee5888a972137d3,
title = "Maintenance management system based on Bayesian networks",
abstract = "With the application of maintenance management system, the daily failure data of airplane components has been collected in great number. The challenge faced currently is how to predict the failure probability of certain components and carry out optimal maintenance strategy (when and how) to reduce the lifecycle cost of the airplane. In this paper, we have presented a proactive maintenance management framework as well as the entire maintenance work flow which guides the establishment of maintenance system in detail. Furthermore, we brought out the procedures of building prognosis Bayesian networks and decision Bayesian networks. The prognosis network which is based on discovered associations from failure data can provide reliable predictions on component failure probability; while the decision network could help to make maintenance decisions balancing among resource availability, repair effect, cost and product risk.",
keywords = "Bayesian networks, Decision making, Failure prognosis, Proactive maintenance",
author = "Zhiqiang Cai and Shudong Sun and Shubin Si and Bernard Yannou",
year = "2008",
doi = "10.1109/ISBIM.2008.28",
language = "英语",
isbn = "9780769535609",
series = "2008 International Seminar on Business and Information Management, ISBIM 2008",
publisher = "IEEE Computer Society",
pages = "42--45",
booktitle = "2008 International Seminar on Business and Information Management, ISBIM 2008",
note = "2008 International Seminar on Business and Information Management, ISBIM 2008 ; Conference date: 19-12-2008 Through 19-12-2008",
}