Utilization of neural networks for the recognition of variance shifts in correlated manufacturing process parameters

DOI10.1080/00207540110071750zbMath1037.90515OpenAlexW2142025954MaRDI QIDQ4443303

Christopher W. Zobel, Q. J. Nottingham, Deborah F. Cook

Publication date: 2001

Published in: International Journal of Production Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207540110071750

zbMATH Keywords

neutral networkmanufacturing industries

Mathematics Subject Classification ID

Production models (90B30)

Related Items (3)

Simultaneous identification of mean shift and correlation change in AR(1) processes ⋮ A hybrid learning-based model for on-line monitoring and diagnosis of out-of-control signals in multivariate manufacturing processes ⋮ Using anMQEchart based on a self-organizing map NN to monitor out-of-control signals in manufacturing processes

Cites Work

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• Control Charts in the Presence of Data Correlation
• X-bar andRcontrol chart interpretation using neural computing
• An integrated neural network approach for simultaneous monitoring of process mean and variance shifts a comparative study
• The determination of mean and/or variance shifts with artificial neural networks

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