Authors:
Victoria Pachón
1
;
Jacinto Mata
1
;
Francisco Roche
1
;
Jose Cristobal Riquelme Santos
2
and
Jose María Tejera
3
Affiliations:
1
Escuela Politécnica Superior, Universidad de Huelva, Spain
;
2
Escuela Técnica Superior de Ingenieros Informáticos, Universidad de Sevilla, Spain
;
3
Atlantic Copper SA., Spain
Keyword(s):
Data Mining, KDD, Industrial Applications of Artificial Intelligence
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence and Decision Support Systems
;
Enterprise Information Systems
;
Industrial Applications of Artificial Intelligence
;
Strategic Decision Support Systems
Abstract:
In the process of smelting copper mineral a large amount of sulphuric dioxide (SO2) is produced. This compound would be highly pollutant if it was emitted to the atmosphere. By means of an acid plant it is possible to transform it into sulphuric acid, using for this a set of chemical and physical processes. In this way we dispose of a marketable product and, at the same time, the environment is protected. However, there are certain situations in which the gases escape to the atmosphere, creating pollutant situations. This would be avoidable if we exactly knew under which circumstances this problem is produced. In this paper we present a practical application of KDD techniques to the chemical industry. By means of the obtained results we show the viability of using automatic classifiers to improve a productive process, with an increase of the production and a decrease of the environmental pollution.