Multi-level opportunistic predictive maintenance for multi-component systems with economic dependence and assembly/disassembly impacts. Dinh, D., Do, P., & Iung, B. Reliability Engineering & System Safety, 217:108055, January, 2022. ![Multi-level opportunistic predictive maintenance for multi-component systems with economic dependence and assembly/disassembly impacts [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex For maintenance optimization of multi-component systems, opportunistic maintenance has been addressed in many studies since it allows considering the advantages of dependences between components in maintenance decision-making process. In the literature, economic dependence, which implies that joint maintenance of several components can reduce the maintenance cost, has been widely studied in the framework of opportunistic maintenance. There are however very few existing studies considering the advantages of structural dependence, whereby maintenance of a component requires disassembly of other components, in maintenance optimization. To face this issue, the objective of this paper is to propose a multi-level opportunistic predictive maintenance approach considering both economic and structural dependence. In that way, the economic and structural dependences between components are firstly formulated. A degradation model considering disassembly impacts is then developed. For opportunistic maintenance decision-making, two opportunistic thresholds are introduced. When corrective/preventive maintenance occurs, the first opportunistic threshold (eRo) is defined to select non-disassembled components for opportunistic maintenance. This first opportunistic decision allows considering the economic dependence between components. In addition, the maintenance of the selected components may require disassembly of other components which could be also good candidates to be opportunistically maintained. So, the second opportunistic threshold, sRo(sRo≥eRo), is then developed to select one or several disassembled components to be opportunistically maintained. To evaluate the performance of the proposed opportunistic maintenance approach, a cost model is developed. Particle swarm optimization algorithm is then applied to find the optimal decision variables. Finally, the proposed opportunistic maintenance approach is illustrated through a conveyor system to show its feasibility and added value in maintenance optimization framework.
@article{dinh_multi-level_2022,
title = {Multi-level opportunistic predictive maintenance for multi-component systems with economic dependence and assembly/disassembly impacts},
volume = {217},
issn = {0951-8320},
url = {https://www.sciencedirect.com/science/article/pii/S0951832021005573},
doi = {10.1016/j.ress.2021.108055},
abstract = {For maintenance optimization of multi-component systems, opportunistic maintenance has been addressed in many studies since it allows considering the advantages of dependences between components in maintenance decision-making process. In the literature, economic dependence, which implies that joint maintenance of several components can reduce the maintenance cost, has been widely studied in the framework of opportunistic maintenance. There are however very few existing studies considering the advantages of structural dependence, whereby maintenance of a component requires disassembly of other components, in maintenance optimization. To face this issue, the objective of this paper is to propose a multi-level opportunistic predictive maintenance approach considering both economic and structural dependence. In that way, the economic and structural dependences between components are firstly formulated. A degradation model considering disassembly impacts is then developed. For opportunistic maintenance decision-making, two opportunistic thresholds are introduced. When corrective/preventive maintenance occurs, the first opportunistic threshold (eRo) is defined to select non-disassembled components for opportunistic maintenance. This first opportunistic decision allows considering the economic dependence between components. In addition, the maintenance of the selected components may require disassembly of other components which could be also good candidates to be opportunistically maintained. So, the second opportunistic threshold, sRo(sRo≥eRo), is then developed to select one or several disassembled components to be opportunistically maintained. To evaluate the performance of the proposed opportunistic maintenance approach, a cost model is developed. Particle swarm optimization algorithm is then applied to find the optimal decision variables. Finally, the proposed opportunistic maintenance approach is illustrated through a conveyor system to show its feasibility and added value in maintenance optimization framework.},
language = {en},
urldate = {2021-11-15},
journal = {Reliability Engineering \& System Safety},
author = {Dinh, Duc-Hanh and Do, Phuc and Iung, Benoit},
month = jan,
year = {2022},
keywords = {Economic dependence, Maintenance optimization, Multi-component system, Opportunistic maintenance, Structural dependence},
pages = {108055},
}
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In the literature, economic dependence, which implies that joint maintenance of several components can reduce the maintenance cost, has been widely studied in the framework of opportunistic maintenance. There are however very few existing studies considering the advantages of structural dependence, whereby maintenance of a component requires disassembly of other components, in maintenance optimization. To face this issue, the objective of this paper is to propose a multi-level opportunistic predictive maintenance approach considering both economic and structural dependence. In that way, the economic and structural dependences between components are firstly formulated. A degradation model considering disassembly impacts is then developed. For opportunistic maintenance decision-making, two opportunistic thresholds are introduced. When corrective/preventive maintenance occurs, the first opportunistic threshold (eRo) is defined to select non-disassembled components for opportunistic maintenance. This first opportunistic decision allows considering the economic dependence between components. In addition, the maintenance of the selected components may require disassembly of other components which could be also good candidates to be opportunistically maintained. So, the second opportunistic threshold, sRo(sRo≥eRo), is then developed to select one or several disassembled components to be opportunistically maintained. To evaluate the performance of the proposed opportunistic maintenance approach, a cost model is developed. Particle swarm optimization algorithm is then applied to find the optimal decision variables. 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When corrective/preventive maintenance occurs, the first opportunistic threshold (eRo) is defined to select non-disassembled components for opportunistic maintenance. This first opportunistic decision allows considering the economic dependence between components. In addition, the maintenance of the selected components may require disassembly of other components which could be also good candidates to be opportunistically maintained. So, the second opportunistic threshold, sRo(sRo≥eRo), is then developed to select one or several disassembled components to be opportunistically maintained. To evaluate the performance of the proposed opportunistic maintenance approach, a cost model is developed. Particle swarm optimization algorithm is then applied to find the optimal decision variables. 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