Knowledge discovery in rubber extrusion processes

  1. Castejón Limas, M. 1
  2. Ordieres Meré, J.B. 1
  3. Alba Elías, F. 1
  4. Martínez de Pisón Ascacibar, F.J. 1
  1. 1 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

Revista:
WSEAS Transactions on Information Science and Applications

ISSN: 1790-0832

Año de publicación: 2006

Volumen: 3

Número: 5

Páginas: 915-920

Tipo: Artículo

SCOPUS: 2-s2.0-33744536512 GOOGLE SCHOLAR

Otras publicaciones en: WSEAS Transactions on Information Science and Applications

Resumen

This paper describes the outcomes of a study that the EDMANS(**) group has recently performed in a rubber extrusion process, focusing on the knowledge discovery phase previous to the system modeling. Some of the tools developed to satisfy the special needs of such a process are also presented: the CiTree algorithm for clustering subpopulations in massive databases and the PAELLA algorithm for outlier detection and data cleaning in non normal samples like those typically found in industrial processes. Finally, the results obtained by these data mining techniques when applied to a real rubber extrusion databases are shown.