Minimum cost replacement and maintenance scheduling in dual-dissimilar-unit standby systems

Recent studies have shown that reusing standby elements during the mission may improve the mission success probability significantly. However, such a benefit cannot be effectively achieved without a careful design of the replacement and maintenance schedule (RMS), which determines work period durations of operating elements and types of maintenance performed for idle elements. This paper makes contributions by modeling and optimizing the RMS for a heterogeneous dual-unit warm standby system with the aim to minimize the total expected mission cost, covering operation, standby and maintenance costs as well as mission failure penalty cost. The two system elements are dissimilar, characterized by different performance, failure time distribution and cost parameters. For a successful mission, a specified amount of work must be accomplished before both elements become failed or unavailable. We propose a new probabilistic model-based methodology for assessing the mission success probability and expected mission cost (EMC) of the considered system. An optimization problem is further formulated and solved to find the optimal RMS minimizing the EMC. A case study of a two-pump oil transfer system is conducted to demonstrate the proposed model and effects of different cost parameters on the optimal RMS solution and corresponding mission success probability and EMC.

Automated summary

Recent studies have shown that reusing standby elements during the mission can significantly improve mission success probability. This paper contributes by modeling and optimizing the replacement and maintenance schedule (RMS) for a dual-unit warm standby system to minimize total expected mission cost, considering operation, standby, maintenance costs, and mission failure penalty cost. The proposed probabilistic model-based methodology assesses mission success probability and expected mission cost, with an optimization problem formulated to find the optimal RMS solution.