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In industry, many systems exhibit load-sharing characteristics. In a load-sharing system, failure of an asset, in addition to affect system reliability, increases the workloads of remaining surviving assets and so their failure rates. When managing such the assets in a system, it is important for decision makers to ensure overall performance of the system, by determining redundancy of assets and a preventive maintenance plan with consideration of load sharing and uncertain environmental conditions. This article proposes an approach for synthetically optimizing redundancy design and age-based preventive maintenance for a load-sharing system with identical assets. A two-stage stochastic programming model with recourse is established, which incorporates risk-aversion preference of decision makers. A decomposition algorithm is developed to solve the joint optimization model, incorporating analytical properties of system failure rate functions and models. A comparative study with deterministic optimization and robust optimization is conducted to demonstrate the advantages of the proposed risk-averse stochastic programming approach. Finally, a numerical study on an effluent treatment system is conducted to analyze the optimal redundancy design and maintenance plan and practical insights.
Hao et al. (Mon,) studied this question.