RESEARCH PAPER
Bi-objective Dynamic Group Maintenance Optimization for a Heterogeneous Two-Component System with Bidirectional Coupling and Economic Dependence: A Rolling Time-Domain Approach Based on NSGA-II
1
Shijiazhuang Campus, Army Engineering University, China
A – Conceptualization; B – Methodology; C – Software; D – Validation; E – Formal analysis; F – Investigation; G – Resources; H – Data curation; I – Writing – original draft; J – Writing – review & editing; K – Visualization; L – Supervision; M – Project administration; N – Funding acquisition
Submission date: 2026-02-13
Final revision date: 2026-05-07
Acceptance date: 2026-06-09
Online publication date: 2026-07-14
KEYWORDS
group maintenanceheterogeneous componentsstochastic dependencieseconomic dependenciesbidirectional coupling
TOPICS
- Reliability modelling for maintenance of technical items
- Safety and risk assessment for maintenance of technical systems
- Monitoring and diagnostics for maintenance of technical systems
- Maintenance economics for machines, devices and technical systems
- Quality and reliability for technical items
- Operation and maintenance processes for technical items
- Physics of Failure and Degradation Modelling
- Reliability, Availability, Maintainability and Safety Analysis
- Maintenance Engineering, Asset Management, Life Cycle Costs and Logistics
- Diagnostics, Condition Monitoring and Fault Detection
ABSTRACT
Existing studies on multi-component maintenance often model component dependence as unidirectional, homogeneous, or independent, which limits their ability to capture bidirectional interactions and their impact on maintenance decisions. This paper proposes a dynamic grouped maintenance optimization model for a heterogeneous two-component system with bidirectional degradation coupling and economic dependence. The model minimizes the long-run system cost rate and unavailability under finite system life and limited maintenance resources. A rolling-horizon method based on NSGA-II is developed to obtain Pareto maintenance decisions at each inspection point, and the model is validated through simulations. Under the same coupling strength, the proposed strategy reduces the long-run cost rate by 26.99%, 10.29%, and 8.93%, and system unavailability by 29.13%, 15.25%, and 12.66%, respectively, compared with benchmark models. Sensitivity analysis further confirms its applicability and robustness, providing decision support for heterogeneous multi-component systems.
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| ISSN: | 1507-2711 |
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