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In rigid PVC foam extrusion, foam density is very crucial in determining the mechanical characteristics of the extruded material and the profitability of the manufacturing process. This paper presents a new application of artificial neural computing in the control of PVC foam density in profile extrusion process. A 3-layer multi-layer perceptron (MLP) artificial neural network was developed to estimate the foam density (weight) based on the known processing conditions; mainly heating zones temperatures and screw speed. The network was developed and tested on a specific formula that is used in wood-like products. A two factorial design of experiment was carried out to determine the significant process variables before training the neural networks using a back propagation algorithm. Finally, a comparison between the true weights, and the estimated weights using artificial neural networks is presented.

Neural Network Approach to Density Control of Rigid PVC Foam in Extrusion Process