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Component Maintenance Strategies and Risk Analysis for Random Shock Effects Considering Maintenance Costs
Chao Zhang 1,2,3
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School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Research Institute for Frontier Science, Beihang University, Beijing 100191, China
Ningbo Institute of Technology, Beihang University, Ningbo 315800, China
School of Management Engineering, Zhengzhou University, Zhengzhou 450001, China
Engineering Technology Department, Old Dominion University, Norfolk, VA 23529, United States
Submission date: 2023-01-26
Final revision date: 2023-02-18
Acceptance date: 2023-03-08
Online publication date: 2023-03-15
Publication date: 2023-03-15
Corresponding author
Chao Zhang   

School of Automation Science and Electrical Engineering, Beihang University, China
Eksploatacja i Niezawodność – Maintenance and Reliability 2023;25(2):162011
Maintenance can improve a system’s reliability in a long operation period or when a component has failed. The reliability modeling method that uses the stochastic process degradation model to describe the system degradation process has been widely used. However, the existing reliability models established using stochastic processes only consider the internal degradation process, and do not fully consider the impact of external random shocks on their reliability modeling. Furthermore, the existing theory of importance does not consider the actual factors of maintenance cost. In this paper, based on the reliability modeling of random processes, the degradation rate under the influence of random shocks is introduced into the time scale function to solve the impact of random shocks on product reliability, and two cost importance measures are proposed to guide the maintenance selection of the components under limited resources in the system.Finally, a subsystem of an aircraft hydraulic system is analyzed to verify the proposed method’s performance.
The authors gratefully express their appreciation for the financial supports from the National Natural Science Foundation of China (Grant No. U2233212, 51875015).
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