Optimization of maintenance strategies for large-scale electromechanical-hydraulic equipment based on task risk classification

Abstract

Large-scale electromechanical-hydraulic equipment is characterized by close coupling among mechanical, electrical, and hydraulic subsystems and by complex maintenance tasks. Conventional fixed-interval maintenance is therefore often unable to balance operational safety with resource efficiency. To address insufficient task-risk differentiation, long maintenance-window occupation, and repeated execution of low-risk tasks in fixed schedules, this paper proposes a maintenance strategy optimization method based on task risk classification. Maintenance tasks are divided into rigid and flexible categories, and a hierarchical reorganization and constrained optimization procedure is used to reduce maintenance-window occupation while maintaining the required minimum safety coverage. Nominal scenarios and Monte Carlo sampling are then used to compare the changes in safety coverage and resource occupation under alternative schemes. The illustrative results show that the reorganized scheme keeps the safety coverage at about 97.1% while reducing the normalized maintenance-window occupation time index to 78.5%, a 21.5% reduction compared with the fixed baseline scheme. The results verify the feasibility of balancing safety coverage and resource occupation with the proposed method and provide a reference for maintenance strategy optimization of large-scale electromechanical-hydraulic equipment under data-limited conditions.