Neural Network Modeling for Paper Property Predictions, 2001 Process Control, Electrical & Info. Conference Proceedings
Sandra Lenz, Renae Koerbitz, John Rudd--Appleton Coated Locks Mill became interested in utilizing neural network based empirical modeling technology to predict and optimize process parameters such as formation, porosity, opacity and strength properties. These models can be used for off-line troubleshooting and for on-line operation.
This paper describes the development and deployment of several of these types of models on multiple machines at the mill. Also discussed will be examples of the use of these models for off-line troubleshooting analysis.
Neural network based empirical modeling technology is a viable technology for the paper industry. It can provide valuable information about key process variables in real time that traditionally are obtained through laboratory results.
Neural Network Modeling for Paper Property Predictions, 2001 Process Control, Electrical & Info. Con
