Temperature Control Optimization in a Steel‐Making Continuous Casting Process Using a Multimodal Deep Learning Approach

2019 ◽  
Vol 90 (12) ◽  
pp. 1900321 ◽  
Author(s):  
Gi Woung Song ◽  
Bayu Adhi Tama ◽  
Jaewan Park ◽  
Jeong Yeon Hwang ◽  
Jonggeun Bang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Continuous Casting ◽  
Temperature Control ◽  
Casting Process ◽  
Learning Approach ◽  
Continuous Casting Process ◽  
Control Optimization ◽  
Steel Making

scholarly journals Spatial and Sequential Deep Learning Approach for Predicting Temperature Distribution in a Steel-Making Continuous Casting Process

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 21953-21965
Author(s):  
Soo Young Lee ◽  
Bayu Adhi Tama ◽  
Changyun Choi ◽  
Jong-Yeon Hwang ◽  
Jonggeun Bang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Temperature Distribution ◽  
Continuous Casting ◽  
Casting Process ◽  
Learning Approach ◽  
Continuous Casting Process ◽  
Steel Making

Effects of Steelmaking Ladle Holding Period on Continuous Casting Yield

2013 ◽  
Vol 824 ◽  
pp. 339-346
Author(s):  
Godspower O. Edafeadhe ◽  
Harold C. Godwin
Keyword(s):  
Social Sciences ◽  
Continuous Casting ◽  
Casting Process ◽  
Holding Time ◽  
Optimum Process ◽  
Continuous Casting Process ◽  
Holding Period ◽  
Monthly Average ◽  
Steel Making ◽  
Casting Yield

The study was undertaken to ascertain the effects of holding time during secondary steel making, casting duration, strand loss per heat, and tonnage of steel returned per heat on continuous casting yield (%). A total of 1910 heats, spanning a period of seven years (41 production months) were used for the study. Monthly tonnage of liquid steel produced and cast and the corresponding yield were computed from the casting reports. Also extracted from the casting reports are the average monthly holding time (mins) during secondary steel making, monthly average heat casting duration (minutes), average strand loss per heat and monthly average tonnage of steel returned per heat. A statistical package for social sciences (SPSS) was used to analyse the data obtained. The yield was found to be negatively correlated to steel holding time during secondary steel making (-0.257 mins), strand loss per heat (-0.753 tons), and tonnage of heat returned per heat (-0.944 tons), but positively correlated to casting duration (0.371 mins). The result showed that increase in holding time during secondary steel making, strand loss per heat and tonnage of steel returned per heat decrease the yield of continuous casting process. The model formulated was able to explain 93.4% of the total variation in the observed yield. Efforts should therefore be made to monitor and reduce these parameters that decrease the yield through proper process control, regular checks of the continuous casting machines, replacement of worn out moulds, and in-house training and retraining of casters for optimum process performance.

The Air Reoxidation and the Formation of Large Inclusions in Continuous Casting Process

1973 ◽  
Vol 59 (1) ◽  
pp. 72-84 ◽  
Author(s):  
Kichinosuke MATSUNAGA ◽  
Chikakazu NAMIKI ◽  
Taiji ARAKI
Keyword(s):  
Continuous Casting ◽  
Casting Process ◽  
Continuous Casting Process
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