Component Maintenance Strategies and Risk Analysis for Random Shock Effects Considering Maintenance Costs

• Autorzy: Zhang Chao , Zhang Yadong , Dui Hongyan , Wang Shaoping , Tomovic Mileta M.

Identyfikatory

DOI

10.17531/ein/162011

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

system reliability; preventive maintenance; importance measure; maintenance cost; random shock

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2023
• Tom: Vol. 25, no. 2
• Strony: art. no. 162011
• Opis fizyczny: Bibliogr. 35 poz., rys., tab., wykr.

Twórcy

autor

Zhang Chao

• 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

• https://orcid.org/0000-0001-9054-5132

autor

Zhang Yadong

• School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China

• https://orcid.org/0000-0003-0133-9009

autor

Dui Hongyan

• School of Management Engineering, Zhengzhou University, Zhengzhou 450001, China

autor

Wang Shaoping

• School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
• Ningbo Institute of Technology, Beihang University, Ningbo 315800, China

• https://orcid.org/0000-0002-8102-3436

autor

Tomovic Mileta M.

• Engineering Technology Department, Old Dominion University, Norfolk, VA 23529, United States

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