A comparative study on modeling of a raw material blending process in cement industry using conventional and intelligent techniques

K. Kizilaslan*, S. Ertugrul, A. Kural, C. Ozsoy

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

7 Citations (Scopus)

Abstract

The task of the raw material blending process in a cement factory is to mix the raw materials in order to produce cement raw meal for the kiln. One of the fundamental problems in the cement manufacture is ensuring that the cement raw meal is of the appropriate chemical composition. A raw meal with a good fineness and well-controlled chemical composition can improve the cement quality and the kiln operation performance. For achieving this purpose, an appropriate modeling of process is the first step to design a control system for the process. This paper summarizes the study of modeling the raw material blending process using intelligent techniques and comparison of results with classical system identification methods.

Original languageEnglish
Pages736-741
Number of pages6
Publication statusPublished - 2003
EventProceedings of 2003 IEEE Conference on Control Applications - Istanbul, Turkey
Duration: 23 Jun 200325 Jun 2003

Conference

ConferenceProceedings of 2003 IEEE Conference on Control Applications
Country/TerritoryTurkey
CityIstanbul
Period23/06/0325/06/03

Keywords

  • Cement industry
  • Neural network
  • Neuro-fuzzy
  • System identification

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