The Application of Frailty Model in Remaining Useful Life Estimation (Case Study: Sungun Copper Mine's Loading System)

Document Type : Mining Engineering Article

Authors

1 Ph.D. Student of Shahrood University of Technology, Shahrood, Iran

2 Faculty of Mining, Petroleum & Geophysics, Shahrood University of Technology, Shahrood, Iran

3 Faculty of Mining, Petroleum & Geophysics, Shahrood University of Technology, Shahrood, Iran

4 UiT The Arctic University of Norway, Langnes, Tromsø, 9037, Norway

5 Assistant professor, Imam Khomeini International University, Qazvin, Iran

Abstract

The Residual Useful Life (RUL) provides an estimate of the amount of remaining useful life before a system failure depends on present conditions and past operating profiles. In this paper, RUL is estimated based on reliability and for convergence to more realistic results, the effect of operating environment conditions in the form of risk factors (covariates) is also involved in the analysis. These environmental conditions are sometimes tangible and "Observable" and sometimes it is not possible to determine and include them in the analysis and are analyzed under the heading of “Un-observed risk factors” using the frailty model. RUL analysis of a case study of the loading system (Shovel Komatsu 1250) of the Sungun copper mine, based on 8-months information, has shown that Weibull mix proportional hazard (W-MPHM) has the best fit on the data. In this model, four factors including shift risk, rock kind, load system type and rainfall with risk rates of 2.66, 3.79, 0.204 and 1.18 have been obtained as the most effective factors. System RUL became zero in the next two scenarios in about 40 hours. Comparing W-MPHM and Ex-PHM over 80 hours showed that the concurrence of the reliability curve in the second model is greater than the first model and in fact, the reliability decline rate is higher at the beginning of the range. This result reflects the impact of intangible risk factors on system performance analysis, regardless of which will result in significant inconsistency of the results.

Keywords

References

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Journal of Modeling in Engineering
Volume 18, Issue 62
November 2020
Pages 129-142

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History

  • Receive Date: 08 December 2019
  • Revise Date: 20 April 2020
  • Accept Date: 01 July 2020

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