Cite this article as: |
An-jun Xu and Yan-ping Bao, Editorial for special issue on metallurgical process engineering and intelligent manufacturing, Int. J. Miner. Metall. Mater., 28(2021), No. 8, pp. 1249-1252. https://doi.org/10.1007/s12613-021-2333-z |
An-jun Xu E-mail: anjunxu@126.com
[1] |
R.Y. Yin, Review on the study of metallurgical process engineering, Int. J. Miner. Metall. Mater., 28(2021), No. 8, p. 1253. doi: 10.1007/s12613-020-2220-z
|
[2] |
L. Lin and J.Q. Zeng, Consideration of green intelligent steel processes and narrow window stability control technology on steel quality, Int. J. Miner. Metall. Mater., 28(2021), No. 8, p. 1264. doi: 10.1007/s12613-020-2246-2
|
[3] |
J.H. Chu and Y.P. Bao, Mn evaporation and denitrification behaviors of molten Mn steel in the vacuum refining with slag, Int. J. Miner. Metall. Mater., 28(2021), No. 8, p. 1288. doi: 10.1007/s12613-021-2311-5
|
[4] |
J.J. Wang, L.F. Zhang, G. Cheng, Q. Ren, and Y. Ren, Dynamic mass variation and multiphase interaction among steel, slag, lining refractory and nonmetallic inclusions: Laboratory experiments and mathematical prediction, Int. J. Miner. Metall. Mater., 28(2021), No. 8, p. 1298. doi: 10.1007/s12613-021-2304-4
|
[5] |
S.W. Wu, J. Yang, and G.M. Cao, Prediction of the Charpy V-notch impact energy of low carbon steel using a shallow neural network and deep learning, Int. J. Miner. Metall. Mater., 28(2021), No. 8, p. 1309. doi: 10.1007/s12613-020-2168-z
|
[6] |
F. Yuan, A.J. Xu, and M.Q. Gu, Development of an improved CBR model for predicting steel temperature in ladle furnace refining, Int. J. Miner. Metall. Mater., 28(2021), No. 8, p. 1321. doi: 10.1007/s12613-020-2234-6
|
[7] |
Y.F. Yan and Z.M. Lü, Multi-objective quality control method for cold-rolled products oriented to customized requirements, Int. J. Miner. Metall. Mater., 28(2021), No. 8, p. 1332. doi: 10.1007/s12613-021-2292-4
|
[8] |
Z.M. Lü, T.R. Jiang, and Z.W. Li, Multiproduct and multistage integrated production planning model and algorithm based on an available production capacity network, Int. J. Miner. Metall. Mater., 28(2021), No. 8, p. 1343. doi: 10.1007/s12613-021-2310-6
|
[9] |
J.P. Yang, Q. Liu, W.D. Guo, and J.G. Zhang, Quantitative evaluation of multi-process collaborative operation in steelmaking–continuous casting sections, Int. J. Miner. Metall. Mater., 28(2021), No. 8, p. 1353. doi: 10.1007/s12613-020-2227-5
|
[10] |
H.N. He, X.C. Wang, G.Z. Peng, D. Xu, Y. Liu, M. Jiang, Z.D. Wu, D. Zhang, and H. Yan, Intelligent logistics system of steel bar warehouse based on ubiquitous information, Int. J. Miner. Metall. Mater., 28(2021), No. 8, p. 1367. doi: 10.1007/s12613-021-2325-z
|
[11] |
Z.J. Xu, Z. Zheng, and X.Q. Gao, Operation optimization of the steel manufacturing process: A brief review, Int. J. Miner. Metall. Mater., 28(2021), No. 8, p. 1274. doi: 10.1007/s12613-021-2273-7
|
[12] |
S. Liu, S. Xie, and Q. Zhang, Multi-energy synergistic optimization in steelmaking process based on energy hub concept, Int. J. Miner. Metall. Mater., 28(2021), No. 8, p. 1378. doi: 10.1007/s12613-021-2281-7
|
[13] |
T. Xu, G. Song, Y. Yang, P.X. Ge, and L.X. Tang, Visualization and simulation of steel metallurgy processes, Int. J. Miner. Metall. Mater., 28(2021), No. 8, p. 1387. doi: 10.1007/s12613-021-2283-5
|