Skip to main content
Log in

Reliability Growth Test Planning and Verification of Commercial Vehicles

  • Published:
Automotive Innovation Aims and scope Submit manuscript

A Correction to this article was published on 31 March 2020

This article has been updated

Abstract

Reliability and durability are two important technical indicators in automobile research and development. A research-and-design and testing organization can increase inherent quality attributes by adopting a systematic approach based on statistical tools and clearly defined processes. The process affects the design phase, validation through testing, and quality assurance in production. On the basis of reliability growth theory and the Duane model, this study established an estimation method for the definition of the target mileage and specific test cycles in reliability growth testing. A construction method for defining test conditions was proposed that adopts the theory of the design of experiments. The simulation was conducted under a variety of typical test conditions including differing operation times, loads, and logistics modes to predict customer use and detect failures. Failure cases were then analyzed in detail. At the same time, a reliability growth prediction model was established on the basis of the initial test data and used for test process tracking and risk control.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Change history

Abbreviations

A/C:

Air conditioning

CN6:

China 6 emission legislation

DOE:

Design of experiments

FR:

Failure rate

IPTV:

Incidents per thousand vehicles

MTBF:

Mean time between failures

n.a.:

Not applicable

RG-relevant:

Reliability growth relevant

References

  1. Bitter, P.: Technical Reliability. Springer, Munich (1986)

    Google Scholar 

  2. Ren, L.M., He, G.W., Zhou, H.J.: Reliability Engineer’s Essential Knowledge Manual. Standards Press of China, Beijing (2009)

    Google Scholar 

  3. Weiss, H.K.: Estimation of reliability growth in a complex system with a Poisson-type failure. J. Oper. Res. 4, 532–545 (1956)

    Article  MATH  Google Scholar 

  4. Guo, Y.: Research on mechanical reliability growth test and growth model. Dissertation, Northeastern University (2009)

  5. Duane, J.T.: Learning curve approach to reliability to reliability monitoring. J. IEEE Trans. Aerosp. 2, 563–566 (1964)

    Article  Google Scholar 

  6. Zhang, L., Huang, M., Liu, T.: Reliability scoring and distribution method for aeroengine. J. Qual. Reliab. 2, 49–52 (2009)

    Google Scholar 

  7. Crow, L.H.: Estimation procedures for the Duane model. ADA019372, pp. 32–44 (1972)

  8. Crow, L.H.: AMSAA reliability growth symposium. ADA027053 (1974)

  9. Crow, L.H.: Reliability analysis for complex, repairable systems. ADA020296 (1975)

  10. Hoang, P.: Handbook of Reliability Engineering. Springer, London (2003)

    Google Scholar 

  11. He, G.F., Xu, H.B.: Reliability Data Collection and Analysis. National Defense Industry Press, Beijing (1995)

    Google Scholar 

  12. Jiang, H., Liu, R.Y.: Methods to estimate location parameters of Weibull distribution with interpolation method. J. Qinghai Univ. 21(3), 53–57 (2003)

    Google Scholar 

  13. Zhu, M.Y.: Parameter estimation of three-parameter Weibull distribution. J. Jiangsu Norm. Univ. Technol. 12(6), 31–34 (2006)

    Google Scholar 

  14. Hu, E.P., Luo, X.B., Liu, G.Q.: Three-parameter Weibull distribution several commonly used parameter estimation methods. J. Shenyang Inst. Technol. 19(3), 88–93 (2000)

    Google Scholar 

  15. Yan, X.D., Ma, X., Zheng, R.Y.: Comparison of parameters estimation methods for 3-parameter Weibull distribution. J. Ningbo Univ. 18(3), 301–305 (2005)

    Google Scholar 

  16. Yang, S.X., Liu, X.: Maintenance cycle optimization method based on NHPP. J. Aviat. Maint. Eng. 3, 42–44 (2019)

    Google Scholar 

  17. Sun, Y.Q.: Research on theory and method of system reliability growth prediction. Dissertation, Harbin University of Science and Technology (2011)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Huang Liyan.

Ethics declarations

Conflict of interest

On behalf of all authors, the corresponding authors state that there is no conflict of interest.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, J., Huang, L., Zhou, R. et al. Reliability Growth Test Planning and Verification of Commercial Vehicles. Automot. Innov. 2, 328–337 (2019). https://doi.org/10.1007/s42154-019-00082-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42154-019-00082-0

Keywords

Navigation