IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v235y2021i3p331-337.html
   My bibliography  Save this article

Evaluation for machine tool components importance based on improved LeaderRank

Author

Listed:
  • Yingzhi Zhang
  • Shubin Liang
  • Jialin Liu
  • Peilong Cao
  • Lan Luan

Abstract

The existence of the failure transitivity of machine tool components makes the fault transfer probability of components demonstrate dynamic time-variability, which affects the importance of components and further affects the machine maintenance cycle. Therefore, studying fault transfer probability and the importance of machine tool components is necessary. In this article, the fault transfer probability of component is defined according to component fault propagation directed graph and component independent fault and related fault model based on time correlation. Assuming that the fault propagation follows the Markov process, the improved LeaderRank algorithm is applied to evaluate the importance of components by introducing background node and calculating failure impact degree of component on the basis of out-degree. Finally, the specific application is verified by taking the fault information of a certain type of machine as an example.

Suggested Citation

  • Yingzhi Zhang & Shubin Liang & Jialin Liu & Peilong Cao & Lan Luan, 2021. "Evaluation for machine tool components importance based on improved LeaderRank," Journal of Risk and Reliability, , vol. 235(3), pages 331-337, June.
  • Handle: RePEc:sae:risrel:v:235:y:2021:i:3:p:331-337
    DOI: 10.1177/1748006X20979437
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X20979437
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1748006X20979437?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Bae, Joonhyun & Kim, Sangwook, 2014. "Identifying and ranking influential spreaders in complex networks by neighborhood coreness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 549-559.
    2. Linyuan Lü & Yi-Cheng Zhang & Chi Ho Yeung & Tao Zhou, 2011. "Leaders in Social Networks, the Delicious Case," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-9, June.
    3. Li, Qian & Zhou, Tao & Lü, Linyuan & Chen, Duanbing, 2014. "Identifying influential spreaders by weighted LeaderRank," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 404(C), pages 47-55.
    4. Leo Katz, 1953. "A new status index derived from sociometric analysis," Psychometrika, Springer;The Psychometric Society, vol. 18(1), pages 39-43, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Zhixiao & Zhao, Ya & Xi, Jingke & Du, Changjiang, 2016. "Fast ranking influential nodes in complex networks using a k-shell iteration factor," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 171-181.
    2. Zareie, Ahmad & Sheikhahmadi, Amir & Fatemi, Adel, 2017. "Influential nodes ranking in complex networks: An entropy-based approach," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 485-494.
    3. Zhu, Canshi & Wang, Xiaoyang & Zhu, Lin, 2017. "A novel method of evaluating key nodes in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 96(C), pages 43-50.
    4. Wei, Bo & Liu, Jie & Wei, Daijun & Gao, Cai & Deng, Yong, 2015. "Weighted k-shell decomposition for complex networks based on potential edge weights," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 420(C), pages 277-283.
    5. Sheikhahmadi, Amir & Nematbakhsh, Mohammad Ali & Shokrollahi, Arman, 2015. "Improving detection of influential nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 833-845.
    6. Xing Tang & Qiguang Miao & Shangshang Yu & Yining Quan, 2016. "A Data-Based Approach to Discovering Multi-Topic Influential Leaders," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-14, July.
    7. Zhou, Ming-Yang & Xiong, Wen-Man & Wu, Xiang-Yang & Zhang, Yu-Xia & Liao, Hao, 2018. "Overlapping influence inspires the selection of multiple spreaders in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 76-83.
    8. Li, Hanwen & Shang, Qiuyan & Deng, Yong, 2021. "A generalized gravity model for influential spreaders identification in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    9. Chaocheng He & Jiang Wu & Qingpeng Zhang, 2021. "Characterizing research leadership on geographically weighted collaboration network," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4005-4037, May.
    10. Yu, Senbin & Gao, Liang & Xu, Lida & Gao, Zi-You, 2019. "Identifying influential spreaders based on indirect spreading in neighborhood," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 418-425.
    11. Xu, Shuang & Wang, Pei, 2017. "Identifying important nodes by adaptive LeaderRank," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 654-664.
    12. Su, Qingyu & Chen, Cong & Huang, Xin & Li, Jian, 2022. "Interval TrendRank method for grid node importance assessment considering new energy," Applied Energy, Elsevier, vol. 324(C).
    13. Ma, Qian & Ma, Jun, 2017. "Identifying and ranking influential spreaders in complex networks with consideration of spreading probability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 312-330.
    14. Wang, Xiaojie & Zhang, Xue & Zhao, Chengli & Xie, Zheng & Zhang, Shengjun & Yi, Dongyun, 2015. "Predicting link directions using local directed path," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 260-267.
    15. Huang, Chuangxia & Wen, Shigang & Li, Mengge & Wen, Fenghua & Yang, Xin, 2021. "An empirical evaluation of the influential nodes for stock market network: Chinese A-shares case," Finance Research Letters, Elsevier, vol. 38(C).
    16. Xiaojie Wang & Xue Zhang & Chengli Zhao & Dongyun Yi, 2016. "Maximizing the Spread of Influence via Generalized Degree Discount," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-16, October.
    17. Sheikhahmadi, Amir & Nematbakhsh, Mohammad Ali & Zareie, Ahmad, 2017. "Identification of influential users by neighbors in online social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 517-534.
    18. Li, Chao & Wang, Li & Sun, Shiwen & Xia, Chengyi, 2018. "Identification of influential spreaders based on classified neighbors in real-world complex networks," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 512-523.
    19. Liu, Ying & Tang, Ming & Zhou, Tao & Do, Younghae, 2016. "Identify influential spreaders in complex networks, the role of neighborhood," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 289-298.
    20. Yang, Xu-Hua & Xiong, Zhen & Ma, Fangnan & Chen, Xiaoze & Ruan, Zhongyuan & Jiang, Peng & Xu, Xinli, 2021. "Identifying influential spreaders in complex networks based on network embedding and node local centrality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:risrel:v:235:y:2021:i:3:p:331-337. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.