Optimizing condition based maintenance decisions

Author

Jardine, Andrew K S

Author_Institution

Toronto Univ., Ont., Canada

fYear

2002

fDate

2002

Firstpage

90

Lastpage

97

Abstract

The paper first reviews common strategies for implementing smart condition monitoring decisions such as trend analysis that is rooted in statistical process control, expert systems, and the use of neural networks. The paper then focuses on current industry-driven research that employs proportional hazards modeling to identify the key risk factors that should be used to identify the health of equipment from amongst those signals that are obtained during condition monitoring. Economic considerations are then blended with the risk estimate to establish optimal condition-based maintenance (CBM) decisions

Keywords

condition monitoring; decision theory; failure analysis; maintenance engineering; optimisation; reliability; risk management; condition based maintenance decisions optimisation; economic considerations; equipment health assessment; proportional hazards modeling; risk estimation; risk factors; smart condition monitoring decisions; trend analysis; Condition monitoring; Cost function; Expert systems; Fuzzy logic; Hazards; Humans; Neural networks; Petroleum; Rivers; Signal processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Reliability and Maintainability Symposium, 2002. Proceedings. Annual

Conference_Location

Seattle, WA

ISSN

0149-144X

Print_ISBN

0-7803-7348-0

Type

conf

DOI

10.1109/RAMS.2002.981625

Filename

981625