IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i19p4083-d1248320.html
   My bibliography  Save this article

Risk Evaluation Method Based on Fault Propagation and Diffusion

Author

Listed:
  • Liming Mu

    (School of Mechatronic Engineering, Xi’an Technological University, Xi’an 710021, China)

  • Yingzhi Zhang

    (School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130022, China)

  • Qiyan Zhang

    (School of Materials Science and Chemical Engineering, Xi’an Technological University, Xi’an 710021, China)

Abstract

The high reliability demand of the machining center emphasizes the accuracy of the fault risk evaluation. In the traditional fault risk evaluation research of the machining center, the influence of fault mode is mostly based on subjective recommendation or does not consider the propagation and diffusion of fault, which makes the risk evaluation results different from the real situation. Therefore, this paper presents a framework to evaluate the fault risk for machining center components. A certain type of machining center is considered as a case study. The fault mode frequency ratio of components is calculated by fault mode analysis. The fault rate calculation is conducted based on the Johnson method. Considering that different fault modes have different influences on fault propagation breadth and depth, the hypergraph theory is used to build a hypernetwork model. The propagation and diffusion influence degree are defined to describe the propagation and diffusion process of faults. Then, the comprehensive influence degree of fault mode is calculated. The risk evaluation is realized by considering the component fault rate, fault mode frequency ratio, and the comprehensive influence degree of fault mode. The method proposed in this paper can provide a reference for the formulation of risk strategies for the machining center.

Suggested Citation

  • Liming Mu & Yingzhi Zhang & Qiyan Zhang, 2023. "Risk Evaluation Method Based on Fault Propagation and Diffusion," Mathematics, MDPI, vol. 11(19), pages 1-16, September.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:19:p:4083-:d:1248320
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/19/4083/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/19/4083/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yifan Chen & Genbao Zhang & Yan Ran, 2019. "Risk Analysis of Coupling Fault Propagation Based on Meta-Action for Computerized Numerical Control (CNC) Machine Tool," Complexity, Hindawi, vol. 2019, pages 1-11, July.
    2. Kwag, Shinyoung & Gupta, Abhinav & Dinh, Nam, 2018. "Probabilistic risk assessment based model validation method using Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 380-393.
    3. Wang, Qianlin & Diao, Xiaoxu & Zhao, Yunfei & Chen, Feng & Yang, Guoan & Smidts, Carol, 2021. "An expert-based method for the risk analysis of functional failures in the fracturing system of unconventional natural gas," Energy, Elsevier, vol. 220(C).
    4. Heidar Mohammadi & Zohreh Fazli & Hiro Kaleh & Hamid Reza Azimi & Saber Moradi Hanifi & Nasrin Shafiee, 2021. "Risk Analysis and Reliability Assessment of Overhead Cranes Using Fault Tree Analysis Integrated with Markov Chain and Fuzzy Bayesian Networks," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-17, October.
    5. Chemweno, Peter & Pintelon, Liliane & Muchiri, Peter Nganga & Van Horenbeek, Adriaan, 2018. "Risk assessment methodologies in maintenance decision making: A review of dependability modelling approaches," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 64-77.
    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. Shinyoung Kwag & Jinsung Kwak & Hwanho Lee & Jinho Oh & Gyeong-Hoi Koo, 2019. "Enhancement in the Seismic Performance of a Nuclear Piping System using Multiple Tuned Mass Dampers," Energies, MDPI, vol. 12(11), pages 1-26, May.
    2. Kwag, Shinyoung & Choi, Eujeong & Eem, Seunghyun & Ha, Jeong-Gon & Hahm, Daegi, 2021. "Toward improvement of sampling-based seismic probabilistic safety assessment method for nuclear facilities using composite distribution and adaptive discretization," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    3. Junzhong Bao & Zhijie Bian & Bitong Li & Yan Li & Yuguang Gong, 2023. "A Hybrid Approach for Quantitative Analysis of Fire Hazards in Enclosed Vehicle Spaces on Ro-ro Passenger Ships," Sustainability, MDPI, vol. 15(17), pages 1-16, August.
    4. Bodda, Saran Srikanth & Gupta, Abhinav & Dinh, Nam, 2020. "Enhancement of risk informed validation framework for external hazard scenario," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    5. Yuegang Song & Ruibing Wu, 2022. "The Impact of Financial Enterprises’ Excessive Financialization Risk Assessment for Risk Control based on Data Mining and Machine Learning," Computational Economics, Springer;Society for Computational Economics, vol. 60(4), pages 1245-1267, December.
    6. Hamzeh Soltanali & Mehdi Khojastehpour & José Torres Farinha & José Edmundo de Almeida e Pais, 2021. "An Integrated Fuzzy Fault Tree Model with Bayesian Network-Based Maintenance Optimization of Complex Equipment in Automotive Manufacturing," Energies, MDPI, vol. 14(22), pages 1-21, November.
    7. Tsoumpris, Charalampos & Theotokatos, Gerasimos, 2023. "A decision-making approach for the health-aware energy management of ship hybrid power plants," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    8. Karar, Ahmed Noaman & Labib, Ashraf & Jones, Dylan, 2023. "Post-warranty maintenance strategy selection using shape packages process," International Journal of Production Economics, Elsevier, vol. 255(C).
    9. Lee, Juseong & Mitici, Mihaela, 2020. "An integrated assessment of safety and efficiency of aircraft maintenance strategies using agent-based modelling and stochastic Petri nets," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    10. Jin, Song & Gong, Jinxin, 2021. "Fragility analysis and probabilistic performance evaluation of nuclear containment structure subjected to internal pressure," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    11. Wang, Chong & Matthies, Hermann G., 2019. "Novel model calibration method via non-probabilistic interval characterization and Bayesian theory," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 84-92.
    12. Liu, Gehui & Chen, Shaokuan & Jin, Hua & Liu, Shuang, 2021. "Optimum opportunistic maintenance schedule incorporating delay time theory with imperfect maintenance," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    13. Takeda, Satoshi & Kitada, Takanori, 2021. "Simple method based on sensitivity coefficient for stochastic uncertainty analysis in probabilistic risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    14. DeJesus Segarra, Jonathan & Bensi, Michelle & Modarres, Mohammad, 2023. "Multi-unit seismic probabilistic risk assessment: A Bayesian network perspective," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    15. Kwag, Shinyoung & Park, Junhee & Choi, In-Kil, 2020. "Development of efficient complete-sampling-based seismic PSA method for nuclear power plant," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    16. Wu, Xingguang & Huang, Huirong & Xie, Jianyu & Lu, Meixing & Wang, Shaobo & Li, Wang & Huang, Yixuan & Yu, Weichao & Sun, Xiaobo, 2023. "A novel dynamic risk assessment method for the petrochemical industry using bow-tie analysis and Bayesian network analysis method based on the methodological framework of ARAMIS project," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    17. Mena, R. & Viveros, P. & Zio, E. & Campos, S., 2021. "An optimization framework for opportunistic planning of preventive maintenance activities," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    18. Yutong Song & Yong Deng, 2019. "A new method to measure the divergence in evidential sensor data fusion," International Journal of Distributed Sensor Networks, , vol. 15(4), pages 15501477198, April.
    19. Liting Jing & Qingqing Xu & Tao Sun & Xiang Peng & Jiquan Li & Fei Gao & Shaofei Jiang, 2020. "Conceptual Scheme Decision Model for Mechatronic Products Driven by Risk of Function Failure Propagation," Sustainability, MDPI, vol. 12(17), pages 1-28, September.
    20. Alexander Brem & Dominic T. J. O’Sullivan & Ken Bruton, 2021. "Advancing the Industrial Sectors Participation in Demand Response within National Electricity Grids," Energies, MDPI, vol. 14(24), pages 1-26, December.

    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:gam:jmathe:v:11:y:2023:i:19:p:4083-:d:1248320. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.