Reconocimiento De Patrones De Procesos Industriales Mediante El Uso De Redes Neuronales Artificiales

Abstract

In this paper have been identified and classified the variables that characterize industrial processes in the metallurgy area, as a strategy for modeling and optimizing these processes, based on data from a set of firms in the central and southern regions of the Santa Fe province in Argentina. A analysis tool integrating artificial neural networks is proposed, particularly using self-organizing maps (SOM). Preliminary results confirm that the approach is able to provide valuable information and offers possibilities for direct application to the local industry.