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Strength of Materials

, Volume 50, Issue 1, pp 151–156 | Cite as

Study on the Failure Mechanism of the Polymorphic Mixture for Remanufactured Machinery Parts

  • C. H. Liu
  • W. Y. Li
  • W. Z. Rao
  • K. He
Article
  • 57 Downloads

The polymorphic mixture failure mode for multiple heterogeneity of remanufactured (RM) machinery parts makes it difficult to assess their lifetime. The Weibull distribution failure model of RM parts (substrate, coating layer, bonding surface and sudden failure) is constructed with failure time statistics of the parts in service, the latter is used to characterize the failure patterns of RM parts. In view of the multiple heterogeneity of RM parts, the Kaplan–Meier type decoupling method is used to analyze four sets of failure statistics, and each state of the Weibull failure function of the above parts is solved. It reveals the in-service failure mechanism of polymorphic mixtures for multiple heterogeneity of RM machinery parts. The validity and feasibility of the model are verified by the case study. Research results provide the theoretical basis for the design and preparation of a RM alloy powder and the improvement of RM technology. Moreover, the method for lifetime prediction and failure time evaluation of RM parts is proposed and validated.

Keywords

remanufacturing Weibull distribution failure time uncertainty alloy powder 

Notes

Acknowledgments

This research was jointly supported by the Research Project (No. 2016jb08) and Support Program (No. SZXYQNL2017005) of Suzhou University, Key Project of Natural Science Research in Universities of Anhui Province of China (No. KJ2017A438), Chinese Postdoctoral Science Foundation (No. 2017M611574), and Humanities and Social Science Research Project of the Ministry of Education of China (No. 17YJC630082).

References

  1. 1.
    B. S. Xu, Theory and Technology of Equipment Remanufacturing Engineering [in Chinese], National Defense Industrial Press, Beijing (2007).Google Scholar
  2. 2.
    C. Liu, “Tolerance redistributing of the reassembly dimensional chain on measure of uncertainty,” Entropy, 18, No. 10, 348 (2016).CrossRefGoogle Scholar
  3. 3.
    C. Liu, M. Liu, and L. Xing, “A research on the uncertainty measure and its application to the journal surface roughness of remanufactured engine crankshaft,” Automot. Eng., 37, No. 3, 341–345 (2015).Google Scholar
  4. 4.
    L. Hua, W. Tian, W. Liao, and Z. Chao, “Remaining life evaluation for remanufacturing blanks based on non-linear continuum fatigue damage model,” J. Mech. Eng., 51, No. 21, 132–136 (2015).CrossRefGoogle Scholar
  5. 5.
    C. Franke, B. Basdere, M. Clupek, and S. Seliger, “Remanufacturing of mobile phones: capacity, program and facility adaptation planning,” Omega, 34, No. 6, 562–570 (2006).CrossRefGoogle Scholar
  6. 6.
    M. Liu, C. Liu, M. Ge, et al., “The online quality control method for reassembly based on state space model,” J. Clean. Prod., 137, 644–651 (2016).CrossRefGoogle Scholar
  7. 7.
    B. Xu, S. Dong, and P. Shi, “States and prospects of China characterised quality guarantee technology system for remanufactured parts,” J. Mech. Eng., 49, No. 20, 84–90 (2013).CrossRefGoogle Scholar
  8. 8.
    H. D. Wang, Z. Zhang, G. Li, et al., “Investigation of contact fatigue failure mode and mechanism of plasma spraying coating,” Tribology, 32, No. 3, 251–257 (2012).Google Scholar
  9. 9.
    F. Li and H. Shen, “Analysis method of reliability in remanufacturing design based on knowledge reusing,” Mach. Tool Hydr., 38, No. 11, 144–146 (2010).Google Scholar
  10. 10.
    Y. Shen, S. Song, Y. Wang, and C. Du, “Reliability of welded surfacing layer for remanufacture of vehicle’s drive axle housing,” China Mech. Eng., 24, No. 5, 676–680 (2013).Google Scholar
  11. 11.
    H. Cao, S. Tong, H. Chen, and L. Shu, “Analysis of remanufacturing process and residual stress of axis parts based on thermal spraying,” China Mech. Eng., 25, No. 24, 3368–3372 (2014).Google Scholar
  12. 12.
    X. L. Lu, H. D. Wang, and B. S. Xu, “Research status of on-line monitoring of remanufacturing parts coatings in service process,” Nondestruct. Test., 35, No. 2, 18–22 (2013).Google Scholar
  13. 13.
    T. Zhang, Automobile Product Remanufacturing Model and Its Reliability Analysis [in Chinese], Jilin University (2011).Google Scholar
  14. 14.
    Y. Zhao, J. Sun, and J. Li, “Research on microstructure properties and wear and corrosion resistance of FeCr repaired coating on KMN steel by laser cladding,” J. Mech. Eng., 51, No. 8, 37–43 (2015).CrossRefGoogle Scholar
  15. 15.
    J. X. Fang, S. Y. Dong, Y. J. Wang, et al., “The effects of solid-state phase transformation upon stress evolution in laser metal powder deposition,” Mater. Design, 87, 807–814 (2015).CrossRefGoogle Scholar
  16. 16.
    S. Wei, Y. Liu, H. Tian, et al., “Microwave absorption property of plasma spray W-type hexagonal ferrite coating,” J. Magn. Magn. Mater., 377, 419–423 (2015).CrossRefGoogle Scholar
  17. 17.
    C. Liu, Research on the On-Line Quality Control Mechanism of Remanufacturing Assembly Process for Complex Mechanical Products under Uncertainty [in Chinese], Hefei Polytechnic University (2016).Google Scholar
  18. 18.
    H. Zhang, J. Yu, S. Hao, and Y. Peng, “Application of electro-magnetic heat effect on arresting the crack in remanufacturing blank,” J. Mech. Eng., 49, No. 7, 21–28 (2013).CrossRefGoogle Scholar
  19. 19.
    G. B. Zhang and S. H. Guo, “Reliability evaluation of machining tool center based on competing Weibull model,” Comput. Integr. Manuf. Syst., 21, No. 1, 180–186 (2015).Google Scholar
  20. 20.
    Q. Wang, “Some large sample results for a class of functionals of Kaplan–Meier estimator,” Acta Math. Sin., 14, No. 2, 191–200 (1998).CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • C. H. Liu
    • 1
    • 2
  • W. Y. Li
    • 1
  • W. Z. Rao
    • 2
  • K. He
    • 1
  1. 1.School of Mechanical and Electronic EngineeringSuzhou UniversitySuzhouChina
  2. 2.Sino-US Global Logistics InstituteShanghai Jiao Tong UniversityShanghaiChina

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