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Sādhanā

, 44:17 | Cite as

Failure rate analysis of Jaw Crusher: a case study

  • R S SinhaEmail author
  • A K Mukhopadhyay
Article
  • 18 Downloads

Abstract

Failure of crusher components has considerable influence on the productivity of a crushing plant. In order to improve performance and operational reliability, its critical components are needed to be identified to make replacement in time before any catastrophic failure happens. Though traditional maintenance practices exist in crushing plants, a methodical analysis of failure trend is imperative to improve operational reliability of this critical equipment. The present paper deals with failure analysis of rock crusher and its critical components using total time on test (TTT)-plot and other statistical tools. TTT-plot has proven to be a useful tool in reliability analysis.

Keywords

Total time on test Jaw Crusher time between failures life data analysis 

Nomenclature

β

shape parameter

η

scale parameter

t

running time of equipment/components

i

number of failure

n

number of observations for time between failures

Ui

ratio of Si/Sn

Si

is the TTT at time, ti

Sn

is the TTT at nth failure

References

  1. 1.
    Kumar U, Klefsjo B and Granholm S 1989 Reliability investigation for a fleet of load haul dump machines in a Swedish mine. Reliab. Eng. Syst. Saf. 26: 341–361CrossRefGoogle Scholar
  2. 2.
    Kevin F, Ron B, Tige C and Nathan W 2002 A failure forecast method based on Weibull and statistical pattern analysis. Proc. Annu. Reliab. Maintainab.  https://doi.org/10.1109/rams.2002.981610
  3. 3.
    Kara M, Mazhac, Kaebernickl H and Ahmedl A 2006 Determining the reuse potential of components based on life cycle data. Manuf. Technol. 54(1): 1–4Google Scholar
  4. 4.
    Epsten and Sobel 1953 Life testing. J. Am. Stat. Assoc. 48: 486–502MathSciNetCrossRefGoogle Scholar
  5. 5.
    Barlow and Campo R 1975 Total time on test processes and applications to failure data analysis. In: Reliability and fault tree analysis SIAM; Philadelphia, pp. 451–481Google Scholar
  6. 6.
    Chacko 2010 On total time on test transforms order. RT&A 04 (19) Vol.1Google Scholar
  7. 7.
    Bengt K 1991 TTT-plotting-a tool for both theoretical and practical problems. J. Stat. Plan. Inference 99: l–10Google Scholar
  8. 8.
    Sun F B and Kececloglu D B 1999 A new method for obtaining the TTT plot for a censored sample. In: Reliability and Maintainability Symposium; Proceedings; pp. 112–117Google Scholar
  9. 9.
    Barlow R E 1972 Statistical inference under order restrictions. Theory Appl. Isot. Regression; (No. 04; QA278. 7, B3)Google Scholar
  10. 10.
    Zhao and Song Y H 2006 Risk assessment of strategies using Total Time on Test transform. IEEE; 1-4244-0493Google Scholar
  11. 11.
    Gupta R C and Michalek J E 1985 Determination of reliability functions by the TTT transform. IEEE Trans. Reliab. 34(2): 175CrossRefGoogle Scholar
  12. 12.
    Pham T P and Turkkan T G 1994 The Lorenz and the scaled total time on test transform curves: a unified approach. IEEE Trans. Reliab. 43(1): 76CrossRefGoogle Scholar
  13. 13.
    Akersten P A 1986 The bivariate TTT-plot—a tool for the study of non-constant failure intensities. In: Proceedings of Society of Reliability Engineers Symposium; SRE 86Google Scholar
  14. 14.
    Chang S C and Li T F 2005 Estimation of component mean lifetimes of a masked system using unclassified system life data. Appl. Math. Comput. 169(2): 797–805MathSciNetzbMATHGoogle Scholar
  15. 15.
    Bergman B and Bengt K 1984 The total time on test concept and its use in reliability theory, operations research. Reliab. Maintainab. 32(3): 596–606MathSciNetCrossRefGoogle Scholar

Copyright information

© Indian Academy of Sciences 2019

Authors and Affiliations

  1. 1.Department of Mining Machinery EngineeringIndian Institute of Technology (Indian School of Mines)DhanbadIndia

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