Abstract
Optimizing iron ore proportion is significant for improving the performances of sintering process, and the cost of iron ores is important for iron and steel company. Linear programming is an effective optimization method, which can consider both the indices of ore proportion and the cost of iron ores at the same time. Therefore, in the present work, aimed for reducing the cost of sintering materials with keeping required indices, the optimizing ore proportion was investigated by linear programming. First, the basic physicochemical properties of seven kinds of iron ores in a sintering plant were tested, including chemical composition, size distribution, and sintering characteristics (assimilation property, fluidity of liquid phase, and self-strength of bonding phase). Then, the constraint conditions were set according to a base period of the plant, and optimizing iron ore proportion by linear programming was carried out. The optimized ore proportion is 11 pct B + 35 pct C + 18 pct D + 7 pct E + 16 pct F + 13 pct G. The cost of mixed ore decreases from 1245.75 CNY/(t-mixed ore) to 1233.89 CNY/(t-mixed ore), decreases by about 12 CNY/(t-mixed ore) after optimization. Finally, the optimized results of linear programming were verified by sinter pot tests. The difference of sinter pot indices between base period and optimized period is not obvious. The vertical sintering speeds in base period and optimized period are 27.37 mm/min and 26.81 mm/min, respectively, and the tumble indices are 75.93 pct and 75.31 pct, respectively. In general, the ore proportioning by linear programming can obviously reduce the cost of iron ores in sintering process with keeping good sintering performances and good quality of sinter.
Similar content being viewed by others
References
Z.W. Yan, J.L. Zhang, Y.P. Zhang, Z.L. Chen, Y.Z. Wang, B. Gao, and Y. Zhang: Chin. J. Eng., 2016, vol. 38, pp. 913–19.
H.P. Li, S.L. Wu, Z.B. Hong, W.L. Zhang, H. Zhou, and M.Y. Kou: Processes, 2019, vol. 7, p. 931.
Z.C. Yang, Z.G. Liu, M.S. Chu, L.H. Gao, C. Feng, and J. Tang: ISIJ Int., 2021, vol. 61, pp. 1431–38.
H. Guo, F.M. Shen, H.Y. Zhang, Q.J. Gao, and X. Jiang: Metals, 2019, vol. 9, p. 510.
G.C. Zhang, G.P. Luo, W. Song, S. Tian, S. Hao, and Q. Ren: Sintering Pelletizing, 2021, vol. 46, pp. 7–13.
F. Wang, J.F. Xiang, Y.F. Guo, and F.Q. Zheng: Iron Steel Res., 2020, vol. 32, pp. 89–95.
Q.J. Gao, H. Wang, X.Y. Pan, X. Jiang, H.Y. Zheng, and F.M. Shen: Powder Technol., 2021, vol. 390, pp. 256–67.
Y.Q. Xie, Z.Z. Zhang, Z.H. Wang, and T.J. Chun: China Metall., 2018, vol. 28, pp. 9–15.
X.F. Lv, H.L. Han, and H.S. He: Int. J. Adv. Mater. Res., 2011, vol. 402, pp. 183–86.
Y.J. Lee and J.H. Lee: Powder Metall., 2021, vol. 64, pp. 235–40.
S.T. Yang, M. Zhou, T. Jiang, and X.X. Xue: Minerals, 2021, vol. 11, p. 515.
D.K. Rajak, M. Singhai, R. Sahu, and S. Hazra: Trans. Indian Inst. Met., 2021, vol. 74, pp. 1611–22.
W.J. Li: Sintering Pelletizing, 1985, vol. 3, pp. 48–52.
B.Y. Gao: Sintering Pelletizing, 2001, vol. 1, pp. 32–34.
D. Oliveira: J. Iron Steel Res. Int., 2012, vol. 19, pp. 1–5.
P.F. Li, S.Y. Tang, L. Guo, F.Q. Zheng, and Y.F. Guo: Sintering Pelletizing, 2021, vol. 46, pp. 15–20.
A.M. Nyembwe and G. Craig: Ironmak. Steelmak., 2014, vol. 41, pp. 173–81.
L. Nie, C. Liu, G. Liu, J. Zhang, Q. Lang, and K. Wu: Ind. Heat., 2021, vol. 50, pp. 18–22.
K. Eiki, S.L. Wu, and O. Yasuo: Tetsu to Hagane, 1991, vol. 77, pp. 56–62.
S.L. Wu, Y. Liu, J.X. Du, K. Mi, and H. Lin: J. Univ. Sci. Technol. Beijing, 2002, vol. 3, pp. 254–57.
M. Todd: Math. Program., 2002, vol. 91, pp. 417–36.
E. Fathy: Alexandria Eng. J., 2022, vol. 61, pp. 10419–32.
X.W. Li, G.F. Yan, and Q.N. Li: Methods of Optimization, Beijing Inst. Technol. Press, Beijing, China, 2018, pp. 36–71.
A. Blass: Contemp. Math., 1984, vol. 31, pp. 31–33.
H. Allen: Am. Math. Mon., 2009, vol. 116, pp. 471–76.
S.I. Gass: SIAM Rev., 1998, vol. 40, pp. 149–52.
R.W. Cottle: SIAM Rev., 2006, vol. 36, pp. 666–68.
E. Buyukkoca, I. Yamada, and I. Kusaba: J. Chem. Eng. Jpn., 1974, vol. 7, pp. 392–94.
A.H. Ansari: Z. Angew. Math. Phys., 2019, vol. 7, pp. 23–30.
A.L. Zhang and H. Tang: J. Kunming Univ. Sci. Technol., 2014, vol. 39, pp. 53–57.
X. Jiang, H.Y. Zhang, H.Y. Zheng, Q.J. Gao, and F.M. Shen: J. Iron Steel Res. Int., 2020, vol. 27, pp. 624–30.
X. Jiang, F.M. Shen, H.S. Han, F. Long, H.Y. Zheng, and Q.J. Gao: Iron Steel, 2019, vol. 54, pp. 13–17.
Q.C. Hu, C.L. Wu, J.H. Sun, N. Wang, and B.S. Hu: Int. J. Miner. Process. Extr. Metall., 2019, vol. 4, pp. 1–6.
Y.Q. Sun, D.H. Liu, L.Y. Sun, Q. Lv, and R. Liu: Int. J. Adv. Mater. Res., 2014, vol. 2951, pp. 1687–90.
T. Deng, X.Y. Cao, and J.C. Wang: China Metall., 2015, vol. 25, pp. 33–37.
K. Junya, K. Eiki, S. Fumio, and K. Takazo: ISIJ Int., 2005, vol. 45, pp. 500–05.
B.G. Ellis, C.E. Loo, and D. Witchard: Ironmak. Steelmak., 2013, vol. 34, pp. 99–108.
M.L. Li, T.J. Chun, and Z.Y. Ruan: Min. Eng., 2022, vol. 20, pp. 40–4.
S.P. Yang, H.J. Liu, H.X. Sun, T.T. Zhang, and S.M. Liu: Materials, 2022, vol. 15, p. 3329.
Acknowledgments
The financial supports by the National Key Research and Development Program of China (Grant No. 2021YFC2902400), the National Natural Science Foundation of China (NSFC 52074074, NSFC 51874080, NSFC 62001312, NSFC 51974073), the Xingliao Talent Project (XLYC2007152), and the Fundamental Research Funds for the Central Universities (N2125036) are much appreciated.
Conflict of interest
The author declares this manuscript has no conflict of interest.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Zhou, Y., Jiang, X., Wang, X. et al. Optimizing Iron Ore Proportion Aimed for Low Cost by Linear Programming Method. Metall Mater Trans B 53, 4075–4086 (2022). https://doi.org/10.1007/s11663-022-02667-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11663-022-02667-3