Volume 7, Issue sup1, January 2014, Pages 68 - 83
Replacement policies for a complex system with unobservable components using dynamic Bayesian networks
- Demet O., Taner Bilgiç
- Corresponding Author
- Demet O.
Available Online 9 January 2017.
- https://doi.org/10.1080/18756891.2014.853933How to use a DOI?
- Maintenace, replacement policy, DBNs, uncertainty modelling, optimization and heuristics
- We study maintenance of a complex dynamic system consisting of ageing and unobservable components under a predetermined threshold reliability level. Our aim is to construct an optimum replacement policy for the components of the system by minimizing total number of replacements or total replacement cost. We represent the problem with dynamic Bayesian networks (DBNs). We prove that under the existence of a predetermined threshold reliability, performing replacements at periods when the system reliability just falls below the threshold assures optimum replacement times. Four component selection approaches and their cost focused versions are proposed to choose the component to replace and are tested on a complex dynamic problem. Their performances are analyzed under various threshold and cost levels.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - JOUR AU - Demet O. AU - Taner Bilgiç PY - 2017 DA - 2017/01 TI - Replacement policies for a complex system with unobservable components using dynamic Bayesian networks JO - International Journal of Computational Intelligence Systems SP - 68 EP - 83 VL - 7 IS - sup1 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2014.853933 DO - https://doi.org/10.1080/18756891.2014.853933 ID - O.2017 ER -