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Maximum likelihood analysis of multi-stress accelerated life test data of series systems with competing log-normal causes of failure

Roy, Soumya and Mukhopadhyay, Chiranjit (2015) Maximum likelihood analysis of multi-stress accelerated life test data of series systems with competing log-normal causes of failure. In: PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY , APR 2015, pp. 119-130. (In Press)

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Official URL: http://dx.doi.org/10.1177/1748006X14565841

Abstract

This article presents frequentist inference of accelerated life test data of series systems with independent log-normal component lifetimes. The means of the component log-lifetimes are assumed to depend on the stress variables through a linear stress translation function that can accommodate the standard stress translation functions in the literature. An expectation-maximization algorithm is developed to obtain the maximum likelihood estimates of model parameters. The maximum likelihood estimates are then further refined by bootstrap, which is also used to infer about the component and system reliability metrics at usage stresses. The developed methodology is illustrated by analyzing a real as well as a simulated dataset. A simulation study is also carried out to judge the effectiveness of the bootstrap. It is found that in this model, application of bootstrap results in significant improvement over the simple maximum likelihood estimates.

Item Type: Conference Proceedings
Additional Information: Copy right for this article belongs to the SAGE PUBLICATIONS LTD, 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND
Keywords: Bootstrap; competing risks; expectation-maximization algorithm; missing information principle; prediction; simulation
Department/Centre: Division of Interdisciplinary Research > Management Studies
Depositing User: Id for Latest eprints
Date Deposited: 28 Apr 2015 07:47
Last Modified: 28 Apr 2015 07:47
URI: http://eprints.iisc.ac.in/id/eprint/51432

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