Joint optimization of condition-based and age-based replacement policy and inventory policy for a two-unit series system

• Published in: Reliability engineering & system safety Vol. 205; p. 107251
• Main Authors: Wang, Jingjing, Qiu, Qingan, Wang, Huanhuan
• Format: Journal Article
• Language: English
• Published: Barking Elsevier Ltd 01.01.2021; Elsevier BV
• Subjects: Age; Age-based replacement policy; Condition-based replacement policy; Inventory policy; Joint optimization; Maintenance costs; Markov processes; Optimization; Reliability engineering; Semi-Markov decision process; Spare parts; Transition probabilities; Turbines; Wind power; Wind turbines; Inventory policy; Condition-based replacement policy; Joint optimization; Semi-Markov decision process; Age-based replacement policy
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2020.107251

•A joint optimization model of condition-based and age-based replacement policy and inventory policy is formulated.•Two failure modes are considered for a series system with two non-identical units.•Semi-Markov decision process is utilized to solve the complex optimization problem. This paper proposes a joint optimization problem of the condition-based and age-based replacement policy and spare parts inventory policy for a series system with two non-identical units. Unit 1 is subject to soft failure and condition-based maintenance actions are adopted. Unit 2 is subject to hard failure and maintenance actions are performed based its usage. Besides the replacement policies, the (0,1) inventory policy is used to order the spare part of unit 1 and the (s,S) inventory policy is employed for unit 2. Unlike the previous studies where the maintenance policy and inventory policy are optimized separately, the replacement and order activities are simultaneously determined at decision epochs in this paper. Moreover, the system state transition probabilities, the expected maintenance costs and expected sojourn times would be derived by utilizing the semi-Markov decision process. The optimal preventive replacement thresholds of both units and the order level of unit 2 are simultaneously determined to minimize the system average maintenance cost per unit time. An illustrative example of a two-unit wind turbine system is used to demonstrate the priority of the proposed joint optimization policy.