Preventive replacement policy of a system considering multiple maintenance actions upon a failure

Self Cite

Maintenance planning of two‐component systems has been extensively studied in recent decades. In the literature, most studies assume that the failure cause of a two‐component system is self‐announcing. In some real applications, the failure cause is masked, and a diagnosis with professional equipment is needed to reveal the failed component. This study investigates a preventive replacement policy of a two‐component series system considering masked causes of failure. When an unexpected failure occurs, we can carry out a diagnosis to reveal the failed component and replace it subsequently, or we can directly replace the whole system without diagnosis. Meanwhile, when we carry out a preventive replacement on a component, the other component can be replaced opportunistically. We formulate the problem as a semi‐Markov decision process, and prove the existence of the stationary optimal policy. The optimal preventive replacement age thresholds for each component and the corresponding optimal maintenance actions upon each failure are jointly obtained to minimize the long‐term average maintenance cost per time unit. A comprehensive numerical study is provided to illustrate the effectiveness of our proposed model.

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Maintenance optimization of a two‐component series system considering masked causes of failure

Hu,

Huang,

Shen

2023

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“…Models related to CBM are usually established through MDP, renewal theory, or regenerative process, which depend on the underlying component degradation characteristics. 1 For the CBM for a system with discrete degradation states, MDP or its variants, for example, semi-MDP, 34,35 hidden-MDP, 36 partially observable MDP, 37 are widely used. If the degradation process is depicted by continuous process, renewal theory or regenerative process is often used to model the problem, [38][39][40] which assumes that the system is restored to as good as new condition immediately after a maintenance action, and thus is not applicable to component-level maintenance problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Joint optimization of condition‐based maintenance and condition‐based reallocation for a system with multiple degrading components

Wang

Yang

2023

Condition‐based maintenance has been studied for managing the degradation of components in a system. However, components in different positions may undergo different workload, leading to imbalanced components degradation. Component reallocation is an effective method to balance the degradation of components in different positions with different degradation rates. Thus, this paper investigates the joint optimization of condition‐based maintenance and condition‐based reallocation for a non‐repairable system with multiple identical and functionally‐exchangeable components that undergo different continuous degradation processes due to different workload. We model this problem through Markov decision process, which is solved by a dynamic programming algorithm, and the objective is to provide the optimal maintenance and reallocation actions exactly for each system state, that is, the joint optimal policy, to minimize the discounted long‐run total cost. Especially, our joint policy is on component‐level and proved to be optimal. Finally, the numerical analysis shows the structural insights and effectiveness of the proposed joint policy, for which the sensitivity analysis on the degradation parameters, setup cost, reallocation cost, and downtime cost is performed. We also propose a new reallocation strategy and show the results and computation time for systems with different scales, which indicates that our model can handle systems with reasonable size.

“…Examples of systems that often undergo TBM in engineering include high-precision boring mills, 11 oil pipelines, 12 and mechanical valves. 13 On the other hand, CBM is typically applied to systems whose degradation states are available. CBM has been increasingly adopted in various fields, including railway, 14 subsea tree systems, 15 and wind turbines.…”

Section: Introductionmentioning

confidence: 99%

“…TBM involves performing a series of maintenance actions at predetermined time epochs. Examples of systems that often undergo TBM in engineering include high‐precision boring mills, 11 oil pipelines, 12 and mechanical valves 13 . On the other hand, CBM is typically applied to systems whose degradation states are available.…”

Section: Introductionmentioning

confidence: 99%

Non‐periodic inspection and replacement policy of system subject to non‐homogeneous gamma degradation process

Yao,

Hu,

et al. 2023

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The non‐homogeneous gamma process can exhibit a convex average trend with a non‐linear shape parameter, providing significant flexibility in fitting an accelerated degradation process. However, few studies have been conducted on the maintenance modeling of systems undergoing a non‐homogeneous gamma degradation process despite its versatility. Meanwhile, most maintenance studies adopt a periodic inspection policy to reveal the degradation level. However, it is reasonable to inspect less frequently when the degradation level of the system is low and to perform inspections more frequently when the degradation level increases. Therefore, we conduct a study on the inspection/replacement policy of systems undergoing a non‐homogeneous gamma degradation process, where three non‐periodic inspection policies are investigated. We formulate the problem as a SMDP framework and present a value iteration algorithm to obtain the optimal action at each decision epoch that minimizes the long‐term average cost. A comprehensive numerical study is provided to illustrate the effectiveness of our proposed model.