DocumentCode
2314453
Title
Machinery Condition Monitoring System Selection A Multi-Objective Decision Approach Using GA
Author
Verma, A.K. ; Srividya, A. ; Ramesh, P.G.
Author_Institution
Indian Inst. of Technol., Mumbai
fYear
2008
fDate
16-18 July 2008
Firstpage
787
Lastpage
792
Abstract
In this paper, a framework for Condition Based Maintenance (CBM) of large engineering systems has been suggested to address the need to optimize the characteristics of both the condition monitoring system and the plant that is being maintained at a macro level. CBM for large engineering systems has been modeled using Markov process. The issues which are critical to CBM, namely, predictability, detectability as well as implications of availability and cost have been considered in the framework to provide effective decision support. The application of the framework has been demonstrated using a numerical example. The trade offs between the Pareto optimal solutions of various objectives have been studied and the effects of variation of the maintenance objective function values with detectability and predictability have been brought out.
Keywords
Markov processes; Pareto analysis; condition monitoring; decision theory; genetic algorithms; maintenance engineering; GA; Markov process; Pareto optimal solutions; large engineering systems; machinery condition monitoring system; multiobjective decision approach; Aerospace engineering; Condition monitoring; Costs; Inspection; Machinery; Maintenance engineering; Markov processes; Power engineering and energy; Reliability engineering; Systems engineering and theory; Condition Based Maintenance; Genetic Algorithms; Multi objective optimisation;
fLanguage
English
Publisher
ieee
Conference_Titel
Emerging Trends in Engineering and Technology, 2008. ICETET '08. First International Conference on
Conference_Location
Nagpur, Maharashtra
Print_ISBN
978-0-7695-3267-7
Electronic_ISBN
978-0-7695-3267-7
Type
conf
DOI
10.1109/ICETET.2008.127
Filename
4580008
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