DocumentCode
2611125
Title
Prediction of system reliability for multiple component repairs
Author
Sun, Yong ; Ma, Lin ; Mathew, Joseph
Author_Institution
Queensland Univ. of Technol., Brisbane
fYear
2007
fDate
2-4 Dec. 2007
Firstpage
1186
Lastpage
1190
Abstract
Optimal asset management in industries requires accurate reliability prediction of complex repairable systems. A Split System Approach (SSA) has previously been presented for predicting the reliability of complex systems with multiple Preventive Maintenance (PM) cycles over a long term horizon. However, the algorithms in that model were derived with an assumption that the same single component is always repaired in all PM actions. This paper extends the model to a scenario where a different single component is repaired each time. This extended model can be used to determine the remaining life of the system and to describe the changes in reliability with PM actions for this scenario. As a result, it can be used to support asset PM decision making over the operation and maintenance phase of the asset. Assets often have a number of vulnerable components, i.e., the lives of these components are much shorter than the lives of the rest of the system. An optimal time of sequential PM actions of these critical components can maximise the useful life of the asset effectively. The model developed in this paper can be used to determine this optimal PM strategy.
Keywords
decision making; mechanical products; preventive maintenance; reliability; PM decision making; SSA; complex repairable systems; maintenance phase; multiple component repairs; multiple preventive maintenance; optimal asset management; split system approach; system reliability prediction; Asset management; Australia; Cyclic redundancy check; Decision making; Predictive models; Preventive maintenance; Production systems; Reliability engineering; Sun; Systems engineering and theory; Preventive maintenance; Production lines; Reliability prediction; Split system approach; Whole life cycle;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Engineering and Engineering Management, 2007 IEEE International Conference on
Conference_Location
Singapore
Print_ISBN
978-1-4244-1529-8
Electronic_ISBN
978-1-4244-1529-8
Type
conf
DOI
10.1109/IEEM.2007.4419379
Filename
4419379
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