Neural Network for Prediction of Thermal Elastomer Quality

Aim To predict the indexes of quality of the thermal elastomer by polymerization process data. Methods Neural networks were used for learning the relationship between the product quality and the polymerization process condition variables in an industrial scale batch polymerization reactor. Results The indexes of quality of the product were inferred with acceptable accuracy from easy to measure reaction process condition variables. Conclusion The method proposed in this paper provides on line soft sensors of the indexes of quality of the thermal elastomal.