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Process monitoring in real time: Empirical bayes approach—discrete case
Author(s) -
Yousry M. A.,
Sturm G. W.,
Feltz C. J.,
Noorossana R.
Publication year - 1991
Publication title -
quality and reliability engineering international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.913
H-Index - 62
eISSN - 1099-1638
pISSN - 0748-8017
DOI - 10.1002/qre.4680070303
Subject(s) - bayes' theorem , posterior probability , statistical process control , computer science , feature (linguistics) , discrete time and continuous time , process (computing) , discrete manufacturing , data mining , algorithm , statistics , bayesian probability , mathematics , artificial intelligence , linguistics , philosophy , production (economics) , economics , macroeconomics , operating system
In this paper an empirical Bayes model is developed to monitor and analyse discrete data generated in a manufacturing process for printed circuit boards. A key feature of this analysis is the use of the current observation at time t and the posterior estimates of the distribution of the proportion nonconforming at time t – 1 to obtain a new, updated estimate of the posterior distribution at time t . The derived approach is widely applicable to statistical process control and provides a simple and fast algorithm for updating.