Title: Bayesian estimation in accelerated life testing

Authors: Sorin Voiculescu, Fabrice Guerin, Mihaela Barreau, Abderafi Charki

Addresses: I.S.T.I.A – Quality and Reliability Department, University of Angers, 62 av Notre-Dame du Lac, 49000 Angers, France. ' I.S.T.I.A – Quality and Reliability Department, University of Angers, 62 av Notre-Dame du Lac, 49000 Angers, France. ' I.S.T.I.A – Quality and Reliability Department, University of Angers, 62 av Notre-Dame du Lac, 49000 Angers, France. ' I.S.T.I.A – Quality and Reliability Department, University of Angers, 62 av Notre-Dame du Lac, 49000 Angers, France

Abstract: A common problem of high-reliability computing is, on the one hand, the magnitude of total testing time required, particularly in the case of high-reliability components; and, on the other hand, the number of devices under testing. In both cases, the objective is to minimise the costs involved in testing without reducing the quality of the data obtained. One solution is based on Accelerated Life Testing (ALT) techniques which permit decreasing the testing time. Another solution is to incorporate prior beliefs, engineering experience, or previous data into the testing framework. It is in this spirit that the use of a Bayesian approach can, in many cases, significantly reduce the number of devices required. This paper presents a study of the Arrhenius-Exponential model by an evaluation of parameters using Maximum Likelihood (ML) and Bayesian methods. A Monte Carlo simulation is performed to examine the asymptotic behaviour of these different estimators.

Keywords: Bayesian estimation; maximum likelihood; accelerated life testing; ALT; Arrhenius exponential model; reliability; Monte Carlo simulation.

DOI: 10.1504/IJPD.2009.023321

International Journal of Product Development, 2009 Vol.7 No.3/4, pp.246 - 260

Available online: 19 Feb 2009 *

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