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The Feasibility of Decreasing FeO Index in the Final Product of Pellet Factory of Golgohar Mining and Industrial Company

Memarian, Moein | 2022

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 55574 (07)
  4. University: Sharif University of Technology
  5. Department: Materials Science and Engineering
  6. Advisor(s): Askari, Masoud; Yoozbashizadeh, Hossein
  7. Abstract:
  8. As one of the most important agglomeration methods, pelletizing has a very important place in the iron and steel production chain. In the present study, the feasibility of improving FeO index in the final product of Pellet Factory No.1 of GolEGohar Mining and Industrial Company was investigated. The remaining FeO in the iron oxide pellet represents the amount of Magnetite that was not oxidized during the pelletizing process. The remaining FeO in the primary Magnetite is a disturbing structure for the direct reduction process and will cause a decrease in the compressive strength of the pellet (CCS) and as a result it will be crushed. Therefore, the percentage of the remaining FeO in the pellet should be reduced as much as possible.The reason for conducting the present research is that, the amount of the remaining FeO in the pellets produced by this factory is much more than the optimal level, i.e. 0.7% by weight, on most days. After the study phase of the research and extracting all the factors that can be effective on the remaining FeO in the pellet factory, a number of 189 variables were obtained, which include process variables in production and laboratory variables. According to the industrial scale of this research, it was concluded that the best method to investigate these factors is the use of data mining techniques, and laboratory investigations on a few limited variables cannot have a significant impact on the research goal.For this reason, after calculating the correlation coefficients of all the variables with the amount of remaining FeO, 40 variables that had the highest correlation with the output were selected and finally a linear Regression model was fitted to the data. By controlling 3 variables of Furnace Hood Temperature in Cooling zone 2, the temperature in the Preheating zone and the temperature of Burner 2, the amount of Residual FeO in the pellet can be adjusted.
  9. Keywords:
  10. Linear Regression ; Data Mining ; Pellets ; Residual Iron Oxid ; Iron Oxid Pellet ; Magnetite Oxidation ; Gol Gohar Iron Ore Mine ; Induration Machine

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