Training artificial neural networks for statistical process control

The use of artificial neural networks (ANNs) in statistical process control (SPC) is studied. An ANN is developed in order to determine the status of a process. The objective of the network is to be able to classify the incoming X-Bar values by indicating the status of the process with the appropria...

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Bibliographic Details
Main Authors: Jacobs, D.A., Luke, S.R.
Format: Conference Proceeding
Language:English
Subjects:
Artificial neural networks
Computer aided manufacturing
Control charts
Diagnostic expert systems
Humans
Jacobian matrices
Management training
Manufacturing processes
Process control
Signal processing
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Description
Summary:The use of artificial neural networks (ANNs) in statistical process control (SPC) is studied. An ANN is developed in order to determine the status of a process. The objective of the network is to be able to classify the incoming X-Bar values by indicating the status of the process with the appropriate rule. The network is presented with ten values which can be out of control, as described by any of the selected rules. The resulting output is the representation of that particular rule. Several simulations are performed. The features of ANNs which make them desirable for SPC applications are summarized.< >
ISSN:0749-6877
2375-5350
DOI:10.1109/UGIM.1993.297059