Application of First-principle Process Control Model in Optimization of a Polymerization Technology

Authors

  • Balázs Balaskó Pannon University, Department of Process Engineering, H-8200 Veszprém, Egyetem Str. 10., Hungary
  • Sándor Németh Pannon University, Department of Process Engineering, H-8200 Veszprém, Egyetem Str. 10., Hungary
  • János Abonyi Pannon University, Department of Process Engineering, H-8200 Veszprém, Egyetem Str. 10., Hungary

DOI:

https://doi.org/10.31914/aak.1841

Keywords:

optimization, process control model

Abstract

Nowadays the optimization of chemical processes is a basic expectation. Chemical industry is one of the most automated industries; therefore it has the potential for continuous improvements by analyzing the enormous quantity of process data with some a priori knowledge and by utilizing the results of previously unknown associations and information about the investigated technology. Beyond data based black- and grey-box modeling techniques, the traditional model-based approach is also needed to analyze and improve the engineering knowledge implemented in the distributed process control system (DCS) as equations and algorithms. This paper deals with the advanced process control system of an operating polymerization technology. Modeling the control system and applying the experience of plant operators, sensibility-analysis between process values and product quality, state-estimating and parameter identification tools, control system and technology qualifying tools or new product operating points could be achieved. The purpose of this paper is to review the possibilities of supervising a complex, hierarchical control system and present its applicability on an real industrial example.

Author Biography

  • Balázs Balaskó, Pannon University, Department of Process Engineering, H-8200 Veszprém, Egyetem Str. 10., Hungary

    corresponding author
    balaskob@fmt.uni-pannon.hu

References

Abonyi, J., Arva, P., Nemeth, S., Vincze, Cs., Bodolai, B., Dobosné, H. Zs., Nagy, G., Németh, M. (2003). Operator Support System for Multi Product Processes - Application to Polyethylene Production, European Symposium on Computer Aided Process Engineering, 14, 347–352. https://doi.org/10.1016/S1570-7946(03)80139-6

Fayyad, U. M., Simoudis, E. (1997). Data mining and knowledge discovery. Tutorial Notes at PADD ’97 – 1st Int. Conf. Prac. App. KDD & Data Mining, London. https://doi.org/10.1023/A:1009771407489

Feil, B., Abonyi, J., Pach, F. P., Nemeth, S., Arva, P., Nemeth, M., Nagy, G. (2004). Semi- mechanistic Models for State Estimation, Soft Sensor for Polymer Melt Index Prediction, Lecture Notes in Computer Science, 3070. 1111–1117. https://doi.org/10.1007/978-3-540-24844-6_174

MacGregor, J. F., Kourti, T. (1995). Statistical process control of multivariate processes, Control Eng. Practice, 3(3), 403–414. https://doi.org/10.1016/0967-0661(95)00014-L

Pach, F. P., Gyenesei, A., Arva, P., Abonyi, J. (2005). Fuzzy Association Rule Mining for Model Structure Identification, 10th Online World Conference on Soft Computing in Industrial Applications. https://doi.org/10.1007/978-3-540-36266-1_25

Pach, F. P., Feil, B., Nemeth, S., Arva, P., Abonyi J. (2006). Process Data Warehousing based Operator Support System for Complex Production Technologies, IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans. https://doi.org/10.1109/TSMCA.2006.859105

Published

2006-10-15

How to Cite

Balaskó, B., Németh, S., & Abonyi, J. (2006). Application of First-principle Process Control Model in Optimization of a Polymerization Technology. Acta Agraria Kaposváriensis, 10(3), 201-209. https://doi.org/10.31914/aak.1841

Most read articles by the same author(s)

1 2 > >>