.png){kind=icon}
.png){kind=icon}
Return
Condition-based midterm maintenance scheduling with rescheduling strategy
.png){kind=icon}
PRE
AI
DOI：10.1016/j.ijepes.2019.105796.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper proposes a condition-based midterm maintenance scheduling with rescheduling strategy. Different from existing methods, the prescheduled maintenance tasks in the proposed method can be rescheduled according to the updated information received from asset condition monitors. To realize the rescheduling strategy, a new decision variable called time-varying maintenance threshold is introduced in the optimization model. When the state measurement of a device is identified to reach the time-varying maintenance threshold, the prescheduled maintenance task should be executed ahead of time to prevent failures. In the proposed method: (1) a stochastic degradation process considering the prescheduled maintenance tasks and the rescheduling strategy is expressed; (2) an optimization model is formulated to minimize the sum of the individual operating risk and the system operating risk through co-optimizing prescheduled maintenance tasks and time-varying maintenance thresholds; (3) a decomposition algorithm is designed to solve the optimization model. Case studies are presented to demonstrate the validity and significant operating risk reduction of the proposed method.
Keywords:
Condition-based midterm maintenance scheduling
Operating risk quantification
Outage model
Rescheduling strategy
Time-varying maintenance threshold
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
I
IF:
5
Papers:
1.1W
Citations:
3.1W