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- W2000884317 abstract "AbstractIn this article we propose a model suitable for statistical process control in short production runs. We wish to detect on-line whether the mean of the process has exceeded a prespecified upper threshold value. The theoretical basis of the model is a Bayesian formulation, leading to a mixture of normal distributions. Issues of decisions about whether the process is within specification and forecasting are addressed. The Kalman filter model is shown to be related to a special case of our model. The calculations are illustrated with a clinical chemistry example. The tool wear problem is another potential candidate for our approach.KEY WORDS : Bayesian statistical process controlKalman filterNormal mixtureTool wear" @default.
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- W2000884317 date "2005-11-01" @default.
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- W2000884317 title "A Bayesian Scheme to Detect Changes in the Mean of a Short-Run Process" @default.
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- W2000884317 doi "https://doi.org/10.1198/004017005000000346" @default.
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