Journal of Failure Analysis and Prevention

, Volume 17, Issue 1, pp 56–67 | Cite as

Operating Environment-Based Availability Importance Measures for Mining Equipment (Case Study: Sungun Copper Mine)

  • Ali Nouri Qarahasanlou
  • Reza Khalokakaie
  • Mohammad Ataei
  • Behzad Ghodrati
Technical Article---Peer-Reviewed
  • 164 Downloads

Abstract

When a system’s performance is inadequate, the concept of availability importance can be used to improve it. The availability of an item depends on the combined aspects of its reliability and maintainability. In a system consisting of many subsystems, the availability of some subsystems is more important to system performance than others. The availability measure determines the priority of availability across subsystems. Most researchers only consider operation time and ignore the influence of the operating environment; therefore, their estimations are not accurate enough. In contrast to previous research, we focus on the influence of the operating environment on the system/subsystem’s characteristics with a view to prioritizing them based on the importance of availability. The paper considers part of the mining fleet system of Sungun copper mine, including the wagon drill, loader, bulldozer, and dump truck subsystems. We identify an ordered list of possibilities for availability improvement and suggest changes or remedial actions for each item to either reduce its failure rate or reduce the time required to repair it.

Keywords

Availability importance measure Operating environment Reliability Maintainability Mining fleet 

References

  1. 1.
    J. Barabady, U. Kumar, Reliability analysis of mining equipment: a case study of a crushing plant at Jajarm Bauxite Mine in Iran. Reliab. Eng. Syst. Saf. 93, 647–653 (2008). doi: 10.1016/j.ress.2007.10.006 CrossRefGoogle Scholar
  2. 2.
    B. Ghodrati, Reliability and operating environment based spare parts planning. Luleå University of Technology, 2005Google Scholar
  3. 3.
    J. Barabady, U. Kumar, Availability allocation through importance measures. Int. J. Qual. Reliab. Manag. 24, 643–657 (2007)CrossRefGoogle Scholar
  4. 4.
    S. Beeson, J.D. Andrews, Importance measures for noncoherent-system analysis. IEEE Trans. Reliab. 52, 301–310 (2003). doi: 10.1109/TR.2003.816397 CrossRefGoogle Scholar
  5. 5.
    Z.W. Birnbaum, On the importance of different components in a multicomponent system. DTIC Document, 1968Google Scholar
  6. 6.
    H.-W. Chang, R.-J. Chen, F.K. Hwang, The structural Birnbaum importance of consecutive-k systems. J. Comb. Optim. 6, 183–197 (2002)CrossRefGoogle Scholar
  7. 7.
    W. Wang, J. Loman, P. Vassiliou, Reliability importance of components in a complex system, IEEE, 2004, pp. 6–11Google Scholar
  8. 8.
    E. Borgonovo, The reliability importance of components and prime implicants in coherent and non-coherent systems including total-order interactions. Eur. J. Oper. Res. 204, 485–495 (2010)CrossRefGoogle Scholar
  9. 9.
    W. Kuo, X. Zhu, Some recent advances on importance measures in reliability. IEEE Trans. Reliab. 61, 344–360 (2012)CrossRefGoogle Scholar
  10. 10.
    H. Ascher, Regression Analysis of Repairable Systems Reliability. Electronic Systems Effectiveness and Life Cycle Costing (Springer, Berlin, 1983), pp. 119–133CrossRefGoogle Scholar
  11. 11.
    S. Kumar, Performance analysis and optimization of some operating systems of a fertilizer plant. Ph.D. Thesis. Department of Mechanical Engineering, National Institute of Technology, Kurukshetra, 2010Google Scholar
  12. 12.
    S.H. Hoseinie, M. Ataei, R. Khalokakaie, U. Kumar, Reliability modeling of water system of longwall shearer machine. Arch. Min. Sci. 56, 291–302 (2011)Google Scholar
  13. 13.
    S.H. Hoseinie, M. Ataei, R. Khalokakaie, B. Ghodrati, U. Kumar, Reliability analysis of drum shearer machine at mechanized longwall mines. J. Qual. Maint. Eng. 18, 98–119 (2012). doi: 10.1108/13552511211226210 CrossRefGoogle Scholar
  14. 14.
    U. Kumar, B. Klefsjö, S. Granholm, Reliability investigation for a fleet of load haul dump machines in a Swedish mine. Reliab. Eng. Syst. Saf. 26, 341–361 (1989). doi: 10.1016/0951-8320(89)90004-5 CrossRefGoogle Scholar
  15. 15.
    B.S. Dhillon, Bibliography of literature on mining equipment reliability. Microelectron. Reliab. 26, 1131–1138 (1986)CrossRefGoogle Scholar
  16. 16.
    B. Dhillon, O. Anude, Mining equipment reliability: a review. Microelectron. Reliab. 32, 1137–1156 (1992)CrossRefGoogle Scholar
  17. 17.
    N. Gorjian, L. Ma, M. Mittinty, P. Yarlagadda, Y. Sun, The explicit hazard model-part 1: theoretical development, IEEE; 2010, pp. 1–10Google Scholar
  18. 18.
    B. Ghodrati, U. Kumar, Reliability and operating environment-based spare parts estimation approach: a case study in Kiruna Mine, Sweden. J. Qual. Maint. Eng. 11, 169–184 (2005)CrossRefGoogle Scholar
  19. 19.
    B. Ghodrati, U. Kumar, D. Kumar, Product support logistics based on product design characteristics and operating environment (Society of Logistics Engineers, Huntsville, 2003), p. 21Google Scholar
  20. 20.
    X. Gao, T. Markeset, Design for production assurance considering influence factors, 2007Google Scholar
  21. 21.
    X. Gao, J. Barabady, T. Markeset, Criticality analysis of a production facility using cost importance measures. Int. J. Syst. Assur. Eng. Manag. 1, 17–23 (2010)CrossRefGoogle Scholar
  22. 22.
    A. Barabadi, J. Barabady, T. Markeset, Maintainability analysis considering time-dependent and time-independent covariates. Reliab. Eng. Syst. Saf. 96, 210–217 (2011)CrossRefGoogle Scholar
  23. 23.
    D.G. Kleinbaum, Survival Analysis (Springer, New York, 2011)Google Scholar
  24. 24.
    A. Barabadi, T. Markeset, Reliability and maintainability performance under Arctic conditions. Int. J. Syst. Assur. Eng. Manag. 2, 205–217 (2011)CrossRefGoogle Scholar
  25. 25.
    M. Rausand, A. Høyland, System Reliability Theory: Models, Statistical Methods, and Applications, vol. 396 (Wiley, Hoboken, 2003)Google Scholar
  26. 26.
    A. Saltelli, S. Tarantola, F. Campolongo, Sensitivity analysis as an ingredient of modeling. Stat. Sci. 15, 377–395 (2000)CrossRefGoogle Scholar
  27. 27.
    A. Saltelli, M. Ratto, S. Tarantola, F. Campolongo, E. Commission, Sensitivity analysis practices: strategies for model-based inference. Reliab. Eng. Syst. Saf. 91, 1109–1125 (2006)CrossRefGoogle Scholar
  28. 28.
    S. Kim, D.M. Frangopol, Optimal planning of structural performance monitoring based on reliability importance assessment. Probab. Eng. Mech. 25, 86–98 (2010)CrossRefGoogle Scholar
  29. 29.
    Minitab n.d. http://www.minitab.com/en-us/. Accessed 10 Nov 2015
  30. 30.
    Reliability Software, Training, Consulting and Related Reliability Engineering Analysis Services from ReliaSoft Corporation n.d. http://www.reliasoft.com/. Accessed 10 Nov 2015
  31. 31.
    IBM—United States n.d. http://www.ibm.com/us-en/. Accessed 10 Nov 2015
  32. 32.
    Wolfram|Alpha: Computational Knowledge Engine n.d. http://www.wolframalpha.com/. Accessed 10 Nov 2015

Copyright information

© ASM International 2016

Authors and Affiliations

  • Ali Nouri Qarahasanlou
    • 1
  • Reza Khalokakaie
    • 1
  • Mohammad Ataei
    • 1
  • Behzad Ghodrati
    • 2
  1. 1.Faculty of Mining, Petroleum & GeophysicsShahrood University of TechnologyShahroodIran
  2. 2.Luleå University of TechnologyLuleåSweden

Personalised recommendations