Estudio comparativo de modelos de caja-negra para la predicción de la fineza del cemento usando medidas de entrada y salida de un circuito de molienda (A comparative study of black-box models for cement fineness prediction using SCADA measurements of a closed circuit grinding)

Luis Ismael Minchala (ismael.minchala@ucuenca.edu.ec)1, Christian Sanchez (christian.sancheza@ucuenca.ec)1, Noe Marcelo Yungaicela (nmarcelo.yungaicelan@ucuenca.ec)1, Alfredo Mora (fmora@iguapan.com.ec)2, Jean Paul Mata (jpaulmata80@hotmail.com)3


1Universidad de Cuenca
2Unión Cementera Nacional
3Universidad Católica de Cuenca

This paper appears in: Revista IEEE América Latina

Publication Date: Feb. 2016
Volume: 14,   Issue: 2 
ISSN: 1548-0992


Abstract:
This paper presents a comparative study of three different modeling techniques for predicting cement fineness using input-output SCADA measurements of the closed circuit grinding in a cement plant. The modeling approaches used are the following: statistical, artificial neural networks (ANN), and adaptive neuro-fuzzy inference system (ANFIS). The data set for generating the predictive models are obtained from a database of the operation of the cement plant, UCEM-Guapan located in Azogues, Ecuador. Online validations of the proposed models allow the selection of the best approach and the most accurate models for cement fineness prediction, Blaine and percentage passing the sieve No. 325.

Index Terms:
black-box model, fineness of cement, prediction   


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