NDLI: Design of reliable system based on Dynamic Bayesian Networks and Genetic Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Dingzhou Cao Shaobai Kan Yu Sun
Copyright Year	2012
Description	Author affiliation: Wayne State University, FAB 1118, 656 W. Kirby, Detroit, MI 48202, USA (Yu Sun) \|\| ReliaSoft Corporation, 1450 S. Eastside Loop, Tucson, Arizona 85710, USA (Dingzhou Cao) \|\| John Jay College of Criminal Justice, CUNY, Room 4226N, 445 W. 59th Street, New York, NY 10019 (Shaobai Kan)
Abstract	Traditional approaches to the design of a reliable system follow system requirement analysis, preliminary design, detail design, and evaluation and redesign phases until a final acceptable design is obtained. However, to achieve a shorter time to market, system reliability concerns should be addressed at the design stage (“design for reliability”). In this paper, we propose a reliability optimization framework based on Dynamic Bayesian Networks (DBN) and Genetic Algorithm (GA) which considers system reliability as a design parameter in design stages and can accelerate the design process of a reliable system. The majority of solution methods for reliability optimization problems are based on simple system structures (series, parallel, or k-out-of-n) without component dependency. In this paper, we extend it to a more complicated system with dynamic behavior. In order to capture the different dynamic behaviors of a system, DBN is used to estimate the system reliability of a potential design. Two basic DBN structures “CHOICE” and “REDUNDANCY” are introduced in this study. GA is developed and integrated into a DBN to find the optimal design. Simulation results show that the integration of GA optimization capabilities with DBN provides a robust, powerful system-design tool. Finally, the proposed method is applied to an example of a cardiac-assist system.
Starting Page	1
Ending Page	6
File Size	614776
Page Count	6
File Format	PDF
ISBN	9781457718496
ISSN	0149144X
e-ISBN	9781457718519
DOI	10.1109/RAMS.2012.6175505
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-01-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Redundancy Logic gates Optimization Reliability engineering Genetic algorithms Power demand System reliability modeling Genetic Algorithm Dynamic Bayesian Networks Reliability optimization
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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