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An empirical bayes strategy for analysing manufacturing data in real time
Author(s) -
Sturm George W.,
Feltz Carol J.,
Yousry Mona A.
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.4680070307
Subject(s) - bayes' theorem , computer science , process (computing) , manufacturing process , statistical process control , data mining , industrial engineering , engineering , artificial intelligence , bayesian probability , materials science , composite material , operating system
This paper discusses and develops a real‐time strategy to monitor manufacturing process control data. The strategy presented in this paper is designed to intercept, analyse and monitor data as measurements are generated from a high‐volume information‐intensive manufacturing process. Empirical Bayes theory is used to develop a method to monitor and analyse continuous type measurements generated by a manufacturing process in real time. Several specific techniques will be proposed for detecting manufacturing process problems and examples of applying these techniques will be shown.