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A complex network-based importance measure for mechatronics systems

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  • Wang, Yanhui
  • Bi, Lifeng
  • Lin, Shuai
  • Li, Man
  • Shi, Hao

Abstract

In view of the negative impact of functional dependency, this paper attempts to provide an alternative importance measure called Improved-PageRank (IPR) for measuring the importance of components in mechatronics systems. IPR is a meaningful extension of the centrality measures in complex network, which considers usage reliability of components and functional dependency between components to increase importance measures usefulness. Our work makes two important contributions. First, this paper integrates the literature of mechatronic architecture and complex networks theory to define component network. Second, based on the notion of component network, a meaningful IPR is brought into the identifying of important components. In addition, the IPR component importance measures, and an algorithm to perform stochastic ordering of components due to the time-varying nature of usage reliability of components and functional dependency between components, are illustrated with a component network of bogie system that consists of 27 components.

Suggested Citation

  • Wang, Yanhui & Bi, Lifeng & Lin, Shuai & Li, Man & Shi, Hao, 2017. "A complex network-based importance measure for mechatronics systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 180-198.
    • Handle: RePEc:eee:phsmap:v:466:y:2017:i:c:p:180-198
    DOI: 10.1016/j.physa.2016.09.006
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    Cited by:

    1. Dui, Hongyan & Wei, Xuan & Xing, Liudong, 2023. "A new multi-criteria importance measure and its applications to risk reduction and safety enhancement," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
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    3. He, Zhichao & Wang, Yanhui & Xia, Weifu & Shen, Yue & Hao, Yucheng & Ren, Qiuyang, 2023. "A method for reliability assessment of complex electromechanical system based on improved network connectivity entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    4. Xia, Weifu & Wang, Yanhui & Hao, Yucheng & He, Zhichao & Yan, Kai & Zhao, Fan, 2024. "Reliability analysis for complex electromechanical multi-state systems utilizing universal generating function techniques," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    5. Lin, Shuai & Jia, Limin & Zhang, Hengrun & Zhang, Pengzhu, 2022. "Reliability of high-speed electric multiple units in terms of the expanded multi-state flow network," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    6. Zhao, Jiangbin & Si, Shubin & Cai, Zhiqiang & Guo, Peng & Zhu, Wenjin, 2020. "Mission success probability optimization for phased-mission systems with repairable component modules," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    7. Chen, Liwei & Gao, Yansan & Dui, Hongyan & Xing, Liudong, 2021. "Importance measure-based maintenance optimization strategy for pod slewing system," Reliability Engineering and System Safety, Elsevier, vol. 216(C).

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