Abstract
One of common problems founded in the rubber compression moulding process is the shrinkage of rubber products leading to the loss of the shape of products. Therefore, this research presents an application of artificial neural network in prediction of the rubber product shrinkage in compression moulding. A back propagation neural network was developed to determine the shrinkage based on the variables of the rubber compound, processing variables like mould temperature and mould sizing variable. A two factorial design of experiment was carried out to obtain the significant variables before training the neural network. The results from the neural network prediction for the inside diameter shrinkage and the cross section diameter shrinkage indicate that architectures 5-11-21-1 and 5-11-16-1 provide a prediction within 95.9% and 96.1% accuracy, respectively.
