Share This Article:

Prediction of Kappa Number in Eucalyptus Kraft Pulp Continuous Digester Using the Box & Jenkins Methodology

Abstract Full-Text HTML XML Download Download as PDF (Size:3789KB) PP. 539-547
DOI: 10.4236/aces.2014.44055    4,283 Downloads   4,998 Views   Citations

ABSTRACT

The quality of the resulting pulping continuous digesters is monitored by measuring the Kappa number, which is a reference of residual lignin. The control of the kappa number is carried out mainly in the top of the digester, therefore it is important to get some indication of this analysis beforehand. In this context, the aim of this work was to obtain a prediction model of the kappa number in advance to the laboratory results. This paper proposes a new approach using the Box & Jenkins methodology to develop a dynamic model for predicting the kappa number from a Kamyr continuous digester from an eucalyptus Kraft pulp mill in Brazil. With a database of 1500 observations over a period of 30 days of operation, some ARMA models were studied, leading to the choice of ARMA (1, 2) as the best forecasting model. After fitting the model, we performed validation with a new set of data from 30 days of operation, achieving a model of 2.7% mean absolute percent error.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

Correia, F. , Hallak d’Angelo, J. , J. Zemp, R. and Mingoti, S. (2014) Prediction of Kappa Number in Eucalyptus Kraft Pulp Continuous Digester Using the Box & Jenkins Methodology. Advances in Chemical Engineering and Science, 4, 539-547. doi: 10.4236/aces.2014.44055.

References

[1] Box, G. and Jenkins, G. (1994) Time Series Analysis: Forecasting and Control. Holden-Day, San Francisco.
[2] Kokurek, M.J., Grace, T.M. and Malcom, E.W., Eds. (1989) Alkaline Pulping, Vol. 5 of Pulp and Paper Manufacture. 3th Edition, Joint Textbook Committee of the Paper Industry, Atlanta.
[3] Smook, G.A. (1988) Handbook for Pulp and Paper Technologists. TAPPI, Atlanta.
[4] Correia, F.M., Colodette, J.L., Regazzi, A.J. and Gomide, J.L. (2011) Eucalyptus Chip Compaction Disturbance Analysis in a Vapor Phase Continuous Digester. Proceedings of the 5th International Colloquium on Eucalyptus Kraft Pulp, P. Seguro, Brasil.
[5] TAPPI—Test methods (2001) TAPPI T 236 OM-06 Kappa Number of Pulp Atlanta, USA.
[6] Gullichsen and Fogelholm, Eds. (1999) Chemical Pulping: Vol. 5 of Papermaking Science and Technology Series. TAPPI Press, Atlanta.
[7] Alexandridis, A., Sarimveis, H., Bafas, G. and Retsina T. (2002) A Neural Network Approach for Modeling and Control of Continuous Digesters. TAPPI Fall Technical Conference, San Diego.
[8] Ahvenlampi, T. and Kortela, U. (2005) Clustering Algorithms in Process Monitoring and Control Application to Continuous Digesters. Informatica, 29, 101-109.
[9] Halmevaara, K. and Hyötyniemi, H. (2005) Performance Optimization of Large Control Systems—Case Study on a Continuous Pulp Digester. Proceedings of the 15th IFAC World Congress, Czech Republic.
[10] Makridakis, S.G., Wheelwright, S.C. and Hyndmann, R.J. (1998) Forecasting: Methods and Applications. 3th Edition, John Wiley and Sons, 642pp.
[11] Berkson, J. (1956) Estimation by Least Squares and by Maximum Likelihood. Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability, Vol. 1: Contributions to the Theory of Statistics, 1-11. University of California Press, Berkeley.
http://projecteuclid.org/download/pdf_1/euclid.bsmsp/1200501642
[12] Bowerman, B.L, O’Connell, R.T. and Koehler, A.B. (2005) Forecasting, Time Series, and Regression: An Applied Approach. 4th Edition, Duxbury Press, 686 p.
[13] Pankratz, A. (2009) Forecasting with Univariate Box-Jenkins Models: Concepts and Cases (Vol. 224). John Wiley & Sons, Hoboken.
[14] Tufa, L.D., Ramasamy, M., Patwardhan, S.C. and Shuhaimi, M. (2010) Development of Box-Jenkins Type Time Series Models by Combining Conventional and Orthonormal Basis Filter Approaches. Journal of Process Control, 20, 108-120.
[15] www.eviews.com

  
comments powered by Disqus

Copyright © 2019 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.