Self-Organizing Maps for Analysis of Expandable Polystyrene Batch Process
Keywords:
Neural networks, self-organizing maps, process control, batch processAbstract
Self-organizing maps (SOM) have been successfully applied in many fields of research. In this paper, we demonstrate the use of SOM-based method for the analysis of Expandable PolyStyrene (EPS) batch process. To this end, a data set of EPS-batch process was used for training a SOM. Reference vectors of the SOM were then classified by K-means algorithm into six clusters, which represent product types of the process. This SOM could also be used for estimating the optimal amounts of the stabilisation agent. The results of a validation data set showed a good agreement between the actual and estimated amounts of the stabilisation agent. Based on this model a Web application was made for test use at the plant. The results indicate that the SOM method can also be efficiently applied to the analysis of the batch process.References
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