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

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  • R Jiang

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.

Suggested Citation

  • R Jiang, 2011. "New approach to the modelling of motor failure data with application to the engine overhaul decision process," Journal of Risk and Reliability, , vol. 225(3), pages 355-363, September.
    • Handle: RePEc:sae:risrel:v:225:y:2011:i:3:p:355-363
    DOI: 10.1177/1748006XJRR324
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    References listed on IDEAS

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    1. Best, D.J. & Rayner, J.C.W., 2007. "Chi-squared components for tests of fit and improved models for the grouped exponential distribution," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3946-3954, May.
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