Title
Combining PHM information and system architecture to support aircraft maintenance planning
Abstract
Aircraft are highly valuable assets and large budgets are spent in preventive and predictive maintenance programs. The application of PHM (Prognostics and Health Management) technologies can be a powerful decision support tool to help maintenance planners. The RUL (Remaining Useful Life) estimations obtained from a PHM system can be used in order to plan in advance for the repair of components before a failure occurs. However, when system architecture is not taken into account, the use of PHM information may lead the operator to rush to replace a component that would not affect immediately the operation of the system under consideration. This paper presents a methodology for decision support in maintenance planning with application in aeronautical systems. The methodology combines system architecture information and RUL estimations for all components comprised in the system under study, allowing the estimation of a RUL value for the whole system. This system level RUL (S-RUL) can be used as support information for identifying the best moment to repair a component. Also, when several components present high degradation levels, the proposed methodology can be used to define a set of components that, when repaired, will bring the whole system to a safe degradation level with lowest cost. A case study is used to illustrate the application of the methodology in a simplified aircraft electrical system.
Year
DOI
Venue
2013
10.1109/SysCon.2013.6549859
SysCon
Keywords
Field
DocType
aerospace industry,aircraft,condition monitoring,maintenance engineering,planning,reliability,phm information,phm technology,rul estimation,aircraft electrical system,aircraft maintenance planning,decision support methodology,predictive maintenance,preventive maintenance,prognostics-and-health management,remaining useful life estimation,system level rul,health monitoring,maintenance planning,prognostics,system arquitecture,inspection,fault trees,prognostics and health management,probability
Prognostics,Systems engineering,Decision support system,Electric power system,Aircraft maintenance,Condition monitoring,Systems architecture,Engineering,Predictive maintenance,Reliability engineering,Maintenance engineering
Conference
ISSN
ISBN
Citations 
1944-7620
978-1-4673-3107-4
3
PageRank 
References 
Authors
0.65
1
6