New approach to the modelling of motor failure data with application to the engine overhaul decision process

Abstract

This paper presents a method to transform data on motor failures, that is extensively used in the literature for the benchmarking of reliability models, into the form of time-to-failure (TTF) data. A normal distribution is appropriate for modelling the TTF data. The estimated mean lives are subsequently fitted to a power-law failure point process model, and the life standard deviation after a failure can be obtained using a recursive relation. These are useful for inferring the life distribution after a future failure. The resulting model is applied to optimize the lifespan and predict the number of overhauls in a given operational interval. The approach developed in this paper is not limited to the specific case for which it is derived; it can be applied to similar problems or situations.

Keywords

motor data failure time time to failure failure point process overhaul decision

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References

Davis

D. J.

An analysis of some failure data. J. Am. Stat. Assoc., 1952, 47, 113–150.

Lindsey

J. K.

Parametric multiplicative intensities models fitted to bus motor failure data. J. Roy. Stat. Soc.: Series C (Appl. Stat.), 1997, 46(2), 245–252.

Blischke

W. R.

Murthy

D. N. P.

Reliability, 2000 (Wiley, New York, New York).

Lai

C. D.

Xie

Stochastic ageing and dependence for reliability, 2006 (Springer, New York, New York).

Best

D. J.

Rayner

J. C. W.

Chi-squared components for tests of fit and improved models for the grouped exponential distribution. Comput. Stat. Data Anal., 2007, 51(8), 3946–3954.

Bain

L. J.

Analysis for the linear failure-rate life-testing distribution. Technometrics, 1974, 16, 551–559.

Smith

R. M.

Bain

L. J.

An exponential power life-testing distribution. Commun. Stat. Part A – Theory Methods, 1975, 4, 469–481.

Mudholkar

G. S.

Srivasta

D. K.

Freimer

Exponentiated Weibull family: a reanalysis of the bus-motor-failure data. Technometrics, 1995, 37(4), 436–445.

Wang

K. S.

H. J.

Hsu

F. S.

Liu

C. S.

Analysis of equivalent dynamic reliability with repairs under partial information. Reliab. Engng Syst. Saf., 2002, 76, 29–42.

10.

Coetzee

J. L.

The role of NHPP models in the practical analysis of maintenance failure data. Reliab. Engng Syst. Saf., 1997, 56, 161–168.

11.

Crow

L. H.

Useful metrics for managing failure mode corrective action. In Proceedings of the Annual Symposiumon Reliability and maintainability, IEEE, January 23 2006, Newport Beach, California, USA, pp. 247–252.

12.

Jiang

A non-parametric approach for modelling reliability growth of complex repairable systems. In Proceedings of the 8th International Conference on Reliability, maintainability and safety, ICRMS 2009, Chengdu, China, 20–24 July 2009, pp. 326–329.

13.

Ebrahimi

Testing exponentiality of the residual life, based on dynamic Kullback–Leibler information. IEEE Trans. Reliab., 1998, 47(2), 197–201.

14.

Siddiqui

M. M.

Caglar

Residual lifetime distribution and its applications. Microelectron. Reliab., 1994, 34(2) 211–227.