TITLE:
Simulation and Techno-Economic Performance of a Novel Charge Calculation and Melt Optimization Planning Model for Steel Making
AUTHORS:
Onigbajumo Adetunji, Saliu Ojo Seidu
KEYWORDS:
Charge Calculation, Process Simulation, Modelling, Induction Furnace, Steel Making, Techno-Economics, Mass and Energy Balance
JOURNAL NAME:
Journal of Minerals and Materials Characterization and Engineering,
Vol.8 No.4,
July
30,
2020
ABSTRACT: Process algorithm, numerical model and techno-economic assessment of
charge calculation and furnace bath optimization for target alloy for induction
furnace-based steelmaking is presented in this study. The developed algorithm
combines the make-to-order (MTO) and charge optimization planning (COP) of the
steel melting shop in the production of target steel composition. Using a
system-level approach, the unit operations involved in the melting process were
analyzed with the purpose of initial charge calculation, prevailing alloy
charge prediction and optimizing the sequence of melt chemistry modification.
The model performance was established using real-time production data from a
cast iron-based foundry with a 1- and 2-ton induction furnace capacity and a
medium carbon-based foundry with a 10- and 15-ton induction furnace capacity. A
simulation engine (CastMELT) was developed in Java IDE with a MySQL database for continuous
interaction with changing process parameters to run the model for validation.
The comparison between the model prediction and production results was analyzed for charge prediction, melt modification
and ferroalloy optimization and possible cost savings. The model performance for elemental charge prediction and calculation purpose with respect to
the charge input (at overall scrap meltdown) gave R-squared, Standard Error,
Pearson correlation and Significance value of (0.934, 0.06, 0.97, 0.0003) for
Carbon prediction, (0.962, 0.06, 0.98, 0.00009) for Silicon prediction, (0.999,
0.048, 0.999, 9E -11) for Manganese Prediction, and (0.997, 0.076, 0.999, 6E -7) for Chromium
prediction respectively. Correlation analysis for melt modification (after
charging of ferroalloy) using the model for after-alloying spark analysis
compared with the target chemistry is at 99.82%. The results validate the
suitability of the developed model as a functional system of induction furnace
melting for combined charge calculation and melt optimization Techno-economic
evaluation results showed that 0.98% - 0.25%
ferroalloy saving per ton of melt is possible using the model. This brings
about an annual production cost savings of 100,000 $/y in foundry A (medium
carbon steel) and 20,000 $/y in foundry B (cast iron) on the use of different
ferroalloy materials.