DocumentCode :
694183
Title :
PHM for complex mining and metallurgy equipment multi-state system based optimal multivariate Bayesian model
Author :
Wu, Jin Jei ; Wu, San Lein ; You, X.X.
Author_Institution :
Dept. of Mech. &Electr. Eng., Jiangxi Univ. of Sci. & Technol., Ganzhou, China
fYear :
2013
fDate :
10-13 Dec. 2013
Firstpage :
1042
Lastpage :
1046
Abstract :
A new insight into PHM (Prognostic and Health Management) for complex mining and metallurgy equipment multi-state system based optimal multivariate bayesian model was studied. With an increasing demand in industry in recent years, multi-state system often subject to multiple bottlenecks such as reliability, availability, maintenance, safety, production planning lots, delivering requirement and so on, thus cause PHM theory for complex multi-state system has become an emerging research topic in both industry and academia. This paper is focused on the optimal multivariate bayesian modeling and developing new PHM methodology for complex mining and metallurgy equipment multi-state system. The method incorporates multivariate bayesian model technique to address key challenges and critical issues in exploring new PHM technology for complex mining and metallurgy equipment multi-state system. An illustrative example from a jaw crusher equipment shows this approach can be used to improve PHM´s performance in terms of the availability, reliability and maintainability of the complex mining and metallurgy equipment multi-state system as well as lower false alarm rate and cost.
Keywords :
maintenance engineering; metallurgy; mining equipment; production planning; reliability; safety; PHM technology; PHM theory; availability; complex metallurgy equipment multistate system; complex mining equipment multistate system; complex multistate system; false alarm rate; maintenance; optimal multivariate Bayesian model; production planning; prognostic and health management; reliability; safety; Availability; Bayes methods; Maintenance engineering; Monitoring; Prognostics and health management; Safety; Complex mining and metallurgy equipment; PHM; multi-state system; multivariate Bayesian model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Engineering and Engineering Management (IEEM), 2013 IEEE International Conference on
Conference_Location :
Bangkok
Type :
conf
DOI :
10.1109/IEEM.2013.6962569
Filename :
6962569
Link To Document :
بازگشت