Failure importance analysis models based on Bayesian network

Author

Si, Shubin ; Liu, Fuhou ; Cai, Zhiqiang

Author_Institution

Dept. of Ind. Eng., Northwestern Polytech. Univ., Xi´´an, China

fYear

2009

fDate

21-23 Oct. 2009

Firstpage

151

Lastpage

154

Abstract

It is very important for the complex equipment to analyze the importance distribution of failure cause, which can make maintenance experts find the weak point of the equipment for diagnosis and improvement. This paper presents the failure importance analysis models based on the failure importance analysis Bayesian network (FIABN) to calculate the failure causes and modes importance. We adopt the immune algorithm to optimize the structure of FIABN. The numerical simulations show FIABN and the failure importance analysis methods are correct and effective.

Keywords

Bayes methods; belief networks; failure analysis; importance sampling; failure importance analysis Bayesian network; failure importance analysis model; immune algorithm; numerical simulation; Algorithm design and analysis; Artificial neural networks; Bayesian methods; Complex networks; Failure analysis; Fuzzy systems; Genetic algorithms; Manufacturing; Numerical simulation; Optimization methods; Bayesian networks; Importance analysis; failure cause and mode; genetic algorithm;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Engineering and Engineering Management, 2009. IE&EM '09. 16th International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-3671-2

Electronic_ISBN

978-1-4244-3672-9

Type

conf

DOI

10.1109/ICIEEM.2009.5344618

Filename

5344618