An adaptive hierarchical Bayes quality measurement plan

Partha Lahiri and Huilin Li

Applied Stochastic Models in Business and Industry, 2009, vol. 25, issue 4, 468-477

Abstract: The quality of a production process is often judged by a quality assurance audit, which is essentially a structured system of sampling inspection plan. The defects of sampled products are assessed and compared with a quality standard, which is determined from a tradeoff among manufacturing costs, operating costs and customer needs. In this paper, we propose a new hierarchical Bayes quality measurement plan that assumes an implicit prior for the hyperparameters. The resulting posterior means and variances are obtained adaptively using a parametric bootstrap method. Published in 2009 by John Wiley & Sons, Ltd.

Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmbi:v:25:y:2009:i:4:p:468-477

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