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Mixing Bayes and empirical Bayes inference to anticipate the realization of engineering concerns about variant system designs

Quigley, J.L. and Walls, L.A. (2011) Mixing Bayes and empirical Bayes inference to anticipate the realization of engineering concerns about variant system designs. Reliability Engineering and System Safety, 96 (8). pp. 933-941. ISSN 0951-8320

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Abstract

Mixing Bayes and Empirical Bayes inference provides reliability estimates for variant system designs by using relevant failure data – observed and anticipated – about engineering changes arising due to modification and innovation. A coherent inference framework is proposed to predict the realization of engineering concerns during product development so that informed decisions can be made about the system design and the analysis conducted to prove reliability. The proposed method involves combining subjective prior distributions for the number of engineering concerns with empirical priors for the non-parametric distribution of time to realize these concerns in such a way that we can cross-tabulate classes of concerns to failure events within time partitions at an appropriate level of granularity. To support efficient implementation, a computationally convenient hypergeometric approximation is developed for the counting distributions appropriate to our underlying stochastic model. The accuracy of our approximation over first-order alternatives is examined, and demonstrated, through an evaluation experiment. An industrial application illustrates model implementation and shows how estimates can be updated using information arising during development test and analysis.

Item type: Article
ID code: 27908
Keywords: empirical bayes inference, reliability engineering, variant system designs, Management. Industrial Management, Applied Mathematics, Industrial and Manufacturing Engineering, Safety, Risk, Reliability and Quality
Subjects: Social Sciences > Industries. Land use. Labor > Management. Industrial Management
Department: Strathclyde Business School > Management Science
Related URLs:
    Depositing user: Mrs Caroline Sisi
    Date Deposited: 06 Jun 2011 16:05
    Last modified: 05 Sep 2014 04:22
    URI: http://strathprints.strath.ac.uk/id/eprint/27908

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