.png){kind=icon}
.png){kind=icon}
Return
Maintenance optimization for systems with heterogeneous multi-unit functional subsystems
.png){kind=icon}
PRE
AI
S
J
X
D
DOI：10.1016/j.ymssp.2026.114794.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Practical engineering systems often incorporate functional subsystems to ensure reliable and stable operation. This study investigates reliability modeling and maintenance decision-making for a system comprising two distinct types of functional subsystems, along with a key subsystem responsible for performing the primary system function. Each functional subsystem consists of heterogeneous component types, with the deterioration of each component represented by discrete degradation states. The different component types contribute to the subsystem’s comprehensive health index with varying importance levels, thereby affecting the key subsystem’s degradation rate and susceptibility to shock damage. Degradation interactions also exist between the functional subsystems, further complicating system reliability. A system reliability model is developed and evaluated using mathematical modeling and Monte Carlo simulation. Based on this model, a maintenance strategy is developed for the system, incorporating cost-saving opportunities from simultaneous maintenance activities at both the subsystem and component levels. Multiple thresholds are defined in terms of the operating time of the key subsystem, functional subsystem health indices, and inter-component degradation states, thereby increasing the optimization complexity as the number of control parameters grows with the number of components and their associated states. To address this complexity, a hybrid approach combining genetic algorithms and Monte Carlo simulation is employed. Case studies based on real-world wind turbine data demonstrate the effectiveness of the proposed method. The proposed approach is compared with an alternative optimization method and validated against benchmark maintenance strategies. Sensitivity analyses further identify the dominant factors among critical parameters and provide guidance for practical industrial applications.
Keywords:
System reliability
Maintenance optimization
Multi-unitfunctionalsubsystems
Journal
IF:
8.9
Papers:
1.2W
Citations:
6.6W
Organization
Cited Papers