Abstract
The need to design and construct structural systems with adequate levels of reliability and redundancy is widely acknowledged. It is as crucial that these desired levels are maintained above target levels throughout the life of the structure. Optimization has served well in providing safer and more economical maintenance strategies. Lifetime maintenance optimization based on system reliability has already been proposed. It is still needed, however, to incorporate redundancy in the lifetime maintenance optimization process. Treating both system reliability and redundancy as criteria in the lifetime optimization process can be highly rewarding. The complexity of the process, however, requires the automation of solving the optimization problem. Genetic algorithms (GAs) are used in this study to obtain solutions to the multi-objective optimization problems considering system reliability, redundancy and life-cycle cost (LCC). An approach to provide the optimization program the ability to optimally select what maintenance actions are applied, when they are applied, and to which structural components they are applied is presented. Two different strategies are proposed. The first strategy has the ability to optimally select mixed maintenance types to apply to different parts of the structure at the same time. This strategy can be used in cases where any combination of different maintenance options can be practically applied to any part of the structure. The application of this strategy on truss structures is shown in a numerical example. The second strategy can be used when a limited number of possibilities of practical maintenance options are available. The application of this strategy to bridge structures is shown in a numerical example. The greatest advantage of the proposed approach (both strategies) is its ability to avoid the application of maintenance interventions to structural components that are not critical.
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