DocumentCode :
3003953
Title :
Hybrid causal models for system diagnostics
Author :
Wang, Chengdong
Author_Institution :
ASML, Norwalk, CT, USA
fYear :
2011
fDate :
24-27 Jan. 2011
Firstpage :
1
Lastpage :
4
Abstract :
System diagnostics, also called system fault diagnostics or fault diagnostics is critical to reduce mean time to repair (MTTR), maintain the availability and keep cost of ownership down. In this paper, a model-based diagnosis approach using hybrid causal model utilizing probabilistic reasoning is introduced. This model has the advantages of being general and integrated with probabilistic reasoning capability. Moreover, soft cause can be included in this hybrid causal mo del as well.
Keywords :
fault diagnosis; inference mechanisms; maintenance engineering; hybrid causal models; mean time to repair; probabilistic reasoning; system fault diagnostics; Bayesian methods; Biological system modeling; Boolean functions; Cognition; Data structures; Fault trees; Reliability; Bayesian belief networks; Diagnostics; Hybrid Causal Model; Reliability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Reliability and Maintainability Symposium (RAMS), 2011 Proceedings - Annual
Conference_Location :
Lake Buena Vista, FL
ISSN :
0149-144X
Print_ISBN :
978-1-4244-8857-5
Type :
conf
DOI :
10.1109/RAMS.2011.5754519
Filename :
5754519
Link To Document :
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