A comparative study of black-box models for cement quality prediction using input-output measurements of a closed circuit grinding

Luis I. Minchala-Avila; Manuel Reinoso-Avecillas; Christian Sanchez; Alfredo Mora; Marcelo Yungaicela; Jean P. Mata-Quevedo

doi:10.1109/SYSCON.2016.7490538

A comparative study of black-box models for cement quality prediction using input-output measurements of a closed circuit grinding

Luis I. Minchala-Avila
, Manuel Reinoso-Avecillas
, Christian Sanchez
, Alfredo Mora
, Marcelo Yungaicela
, Jean P. Mata-Quevedo

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

3 Citas (Scopus)

Resumen

This paper presents the methodology of design of three different modeling techniques for predicting cement quality using input-output measurements of the closed circuit grinding in a cement plant. The modeling approaches used are: statistical, artificial neural networks (ANN), and adaptive neuro-fuzzy inference systems (ANFIS). The data set for generating the predictive models are obtained from a database of the operation of the cement plant, UCEM-Guapan. An OPC (OLE for process control) network configuration in the SCADA system allows online validations of the proposed models in order to select the best approach for real-time prediction of cement quality.

Idioma original	Inglés
Título de la publicación alojada	10th Annual International Systems Conference, SysCon 2016 - Proceedings
Editorial	Institute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)	9781467395182
DOI	https://doi.org/10.1109/SYSCON.2016.7490538
Estado	Publicada - 13 jun. 2016
Evento	10th Annual International Systems Conference, SysCon 2016 - Orlando, Estados Unidos Duración: 18 abr. 2016 → 21 abr. 2016

Serie de la publicación

Nombre	10th Annual International Systems Conference, SysCon 2016 - Proceedings

Conferencia

Conferencia	10th Annual International Systems Conference, SysCon 2016
País/Territorio	Estados Unidos
Ciudad	Orlando
Período	18/04/16 → 21/04/16

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

ODS 9: Industria, innovación e infraestructura

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10.1109/SYSCON.2016.7490538

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Minchala-Avila, L. I., Reinoso-Avecillas, M., Sanchez, C., Mora, A., Yungaicela, M., & Mata-Quevedo, J. P. (2016). A comparative study of black-box models for cement quality prediction using input-output measurements of a closed circuit grinding. En 10th Annual International Systems Conference, SysCon 2016 - Proceedings Artículo 7490538 (10th Annual International Systems Conference, SysCon 2016 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SYSCON.2016.7490538

Minchala-Avila, Luis I. ; Reinoso-Avecillas, Manuel ; Sanchez, Christian et al. / A comparative study of black-box models for cement quality prediction using input-output measurements of a closed circuit grinding. 10th Annual International Systems Conference, SysCon 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. (10th Annual International Systems Conference, SysCon 2016 - Proceedings).

@inproceedings{7a0db81f476f487796a8617c97fa47ad,

title = "A comparative study of black-box models for cement quality prediction using input-output measurements of a closed circuit grinding",

abstract = "This paper presents the methodology of design of three different modeling techniques for predicting cement quality using input-output measurements of the closed circuit grinding in a cement plant. The modeling approaches used are: statistical, artificial neural networks (ANN), and adaptive neuro-fuzzy inference systems (ANFIS). The data set for generating the predictive models are obtained from a database of the operation of the cement plant, UCEM-Guapan. An OPC (OLE for process control) network configuration in the SCADA system allows online validations of the proposed models in order to select the best approach for real-time prediction of cement quality.",

keywords = "adaptive neuro-fuzzy inference system, artificial neural networks, black-box model, Fineness of the cement",

author = "Minchala-Avila, \{Luis I.\} and Manuel Reinoso-Avecillas and Christian Sanchez and Alfredo Mora and Marcelo Yungaicela and Mata-Quevedo, \{Jean P.\}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 10th Annual International Systems Conference, SysCon 2016 ; Conference date: 18-04-2016 Through 21-04-2016",

year = "2016",

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doi = "10.1109/SYSCON.2016.7490538",

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Minchala-Avila, LI, Reinoso-Avecillas, M, Sanchez, C, Mora, A, Yungaicela, M & Mata-Quevedo, JP 2016, A comparative study of black-box models for cement quality prediction using input-output measurements of a closed circuit grinding. En 10th Annual International Systems Conference, SysCon 2016 - Proceedings., 7490538, 10th Annual International Systems Conference, SysCon 2016 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 10th Annual International Systems Conference, SysCon 2016, Orlando, Estados Unidos, 18/04/16. https://doi.org/10.1109/SYSCON.2016.7490538

A comparative study of black-box models for cement quality prediction using input-output measurements of a closed circuit grinding. / Minchala-Avila, Luis I.; Reinoso-Avecillas, Manuel; Sanchez, Christian et al.
10th Annual International Systems Conference, SysCon 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. 7490538 (10th Annual International Systems Conference, SysCon 2016 - Proceedings).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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T1 - A comparative study of black-box models for cement quality prediction using input-output measurements of a closed circuit grinding

AU - Minchala-Avila, Luis I.

AU - Reinoso-Avecillas, Manuel

AU - Sanchez, Christian

AU - Mora, Alfredo

AU - Yungaicela, Marcelo

AU - Mata-Quevedo, Jean P.

PY - 2016/6/13

Y1 - 2016/6/13

N2 - This paper presents the methodology of design of three different modeling techniques for predicting cement quality using input-output measurements of the closed circuit grinding in a cement plant. The modeling approaches used are: statistical, artificial neural networks (ANN), and adaptive neuro-fuzzy inference systems (ANFIS). The data set for generating the predictive models are obtained from a database of the operation of the cement plant, UCEM-Guapan. An OPC (OLE for process control) network configuration in the SCADA system allows online validations of the proposed models in order to select the best approach for real-time prediction of cement quality.

AB - This paper presents the methodology of design of three different modeling techniques for predicting cement quality using input-output measurements of the closed circuit grinding in a cement plant. The modeling approaches used are: statistical, artificial neural networks (ANN), and adaptive neuro-fuzzy inference systems (ANFIS). The data set for generating the predictive models are obtained from a database of the operation of the cement plant, UCEM-Guapan. An OPC (OLE for process control) network configuration in the SCADA system allows online validations of the proposed models in order to select the best approach for real-time prediction of cement quality.

KW - adaptive neuro-fuzzy inference system

KW - artificial neural networks

KW - black-box model

KW - Fineness of the cement

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DO - 10.1109/SYSCON.2016.7490538

M3 - Contribución a la conferencia

AN - SCOPUS:84979279823

T3 - 10th Annual International Systems Conference, SysCon 2016 - Proceedings

BT - 10th Annual International Systems Conference, SysCon 2016 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 10th Annual International Systems Conference, SysCon 2016

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Minchala-Avila LI, Reinoso-Avecillas M, Sanchez C, Mora A, Yungaicela M, Mata-Quevedo JP. A comparative study of black-box models for cement quality prediction using input-output measurements of a closed circuit grinding. En 10th Annual International Systems Conference, SysCon 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2016. 7490538. (10th Annual International Systems Conference, SysCon 2016 - Proceedings). doi: 10.1109/SYSCON.2016.7490538

A comparative study of black-box models for cement quality prediction using input-output measurements of a closed circuit grinding

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