Condition-based maintenance optimisation without a predetermined strategy structure for a two-component series system


Autoria(s): Zhang, Zhisheng; Zhou, Yifan; Sun, Yong; Ma, Lin
Data(s)

2012

Resumo

Most existing research on maintenance optimisation for multi-component systems only considers the lifetime distribution of the components. When the condition-based maintenance (CBM) strategy is adopted for multi-component systems, the strategy structure becomes complex due to the large number of component states and their combinations. Consequently, some predetermined maintenance strategy structures are often assumed before the maintenance optimisation of a multi-component system in a CBM context. Developing these predetermined strategy structure needs expert experience and the optimality of these strategies is often not proofed. This paper proposed a maintenance optimisation method that does not require any predetermined strategy structure for a two-component series system. The proposed method is developed based on the semi-Markov decision process (SMDP). A simulation study shows that the proposed method can identify the optimal maintenance strategy adaptively for different maintenance costs and parameters of degradation processes. The optimal maintenance strategy structure is also investigated in the simulation study, which provides reference for further research in maintenance optimisation of multi-component systems.

Identificador

http://eprints.qut.edu.au/59401/

Publicador

EIN

Relação

http://www.ein.org.pl/pl-2012-02-05

Zhang, Zhisheng, Zhou, Yifan, Sun, Yong, & Ma, Lin (2012) Condition-based maintenance optimisation without a predetermined strategy structure for a two-component series system. Maintenance and Reliability, 14(2), pp. 120-129.

Direitos

Copyright 2012 EIN

Fonte

School of Chemistry, Physics & Mechanical Engineering; Faculty of Built Environment and Engineering; Science & Engineering Faculty

Palavras-Chave #semi-Markov decision process #condition-based maintenance #multi-component system
Tipo

Journal Article