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

•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 propos...

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Published inReliability engineering & system safety Vol. 205; p. 107251
Main Authors Wang, Jingjing, Qiu, Qingan, Wang, Huanhuan
Format Journal Article
LanguageEnglish
Published Barking Elsevier Ltd 01.01.2021
Elsevier BV
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Abstract •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.
AbstractList 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.
•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.
ArticleNumber 107251
Author Wang, Jingjing
Wang, Huanhuan
Qiu, Qingan
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  givenname: Qingan
  surname: Qiu
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  email: Qinganqiu@bit.edu.cn
  organization: School of Management and Economics, Beijing Institute of Technology, 100081, China
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  givenname: Huanhuan
  surname: Wang
  fullname: Wang, Huanhuan
  organization: School of Energy and Environment, City University of Hong Kong, Kowloon, Hong Kong
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Keywords Inventory policy
Condition-based replacement policy
Joint optimization
Semi-Markov decision process
Age-based replacement policy
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Snippet •A joint optimization model of condition-based and age-based replacement policy and inventory policy is formulated.•Two failure modes are considered for a...
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...
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SubjectTerms 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
Title Joint optimization of condition-based and age-based replacement policy and inventory policy for a two-unit series system
URI https://dx.doi.org/10.1016/j.ress.2020.107251
https://www.proquest.com/docview/2505725543
Volume 205
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