Process monitoring in real time: Empirical bayes approach—discrete case | Zendy

Yousry M. A. | Zendy; Sturm G. W. | Zendy; Feltz C. J. | Zendy; Noorossana R. | Zendy

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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.

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