DocumentCode :
629571
Title :
An intelligent approach to optimal predictive maintenance strategy defining
Author :
Mustakerov, Ivan ; Borissova, Daniela
Author_Institution :
Dept. Inf. Processes & Decision Support Syst., Inst. of Inf. & Commun. Technol., Sofia, Bulgaria
fYear :
2013
fDate :
19-21 June 2013
Firstpage :
1
Lastpage :
5
Abstract :
The rapid growth of industries has complicated the systems functioning and has intensified the maintenance process. This emphasizes the need for effective maintenance planning. The improvement in maintenance technology relies on predictive maintenance, which is based on the determination of a machine condition while in operation. Maintenance planning is complex problem involving condition monitoring and expert knowledge. In the paper, an intelligent approach to optimal predictive maintenance strategy defining is proposed. It is based on methodology for predictive maintenance that increases reliability by determining the optimal maintenance strategy. For the goal, an algorithm based on cost-benefit analysis and optimization tasks solution is developed. The proposed approach to optimal predictive maintenance is demonstrated on the example of real vibrating feeder data. The results of numerical illustration show the applicability of intelligent decision making for optimal predictive maintenance strategy defining.
Keywords :
condition monitoring; cost-benefit analysis; decision making; knowledge engineering; maintenance engineering; mechanical engineering computing; optimisation; reliability; vibrations; cost-benefit analysis; expert knowledge; intelligent decision making; machine condition monitoring; maintenance planning; optimal predictive maintenance strategy; optimization task solution; reliability enhancement; vibrating feeder data; Condition monitoring; Decision making; Monitoring; Optimization; Prediction algorithms; Predictive maintenance; component predictive maintenance strategy; cost-benefit evaluations; intelligent decision making; optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovations in Intelligent Systems and Applications (INISTA), 2013 IEEE International Symposium on
Conference_Location :
Albena
Print_ISBN :
978-1-4799-0659-8
Type :
conf
DOI :
10.1109/INISTA.2013.6577666
Filename :
6577666
Link To Document :
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