Parameter optimization of Mg reduction by thermo-silicon method using Taguchi method, grey relational analysis and preference selection index

Abstract This study used Taguchi L16 design to optimize four key variables including reduction temperature, Fe-Si molar ratio, CaF 2 content, and pelletizing pressure for the production of magnesium from Vietnamese dolomite via the silicothermal process. Performance was evaluated by reduction efficiency, product magnesium purity, and ferrosilicon utilisation ratio. Experimental data were analysed using Taguchi-Grey Relational Analysis with Principal Component Analysis and Preference Selection Index. Grey Relational Analysis method determined that the reduction temperature of 1250 °C, Fe-Si molar ratio of 1.3, CaF 2 ratio of 4% and pelletizing force of 120 MPa were optimal, while the Preference Selection Index method suggested a reduction temperature of 1300 °C, Fe-Si molar ratio of 1.3, CaF 2 ratio of 5% and pelletizing force of 80 MPa. Both methods agree that reduction temperature has the greatest effect on yield, with Fe-Si and CaF 2 ratios having a moderate effect and pelletizing pressure having a negligible effect at high reduction temperatures. An Fe-Si ratio of 1.3 consistently production efficiency and reducing agent costs. The results demonstrates the efficacy of multi-criteria decision-making techniques in refining complex metallurgical processes and elucidates the interdependencies among operating parameters, offering actionable insights to enhance magnesium yield and ferrosilicon efficiency.

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Publication Details

Journal
Materials Research Express
Published
2025-06-27
DOI
https://doi.org/10.1088/2053-1591/ade931
Primary Topic
Surface Treatment and Coatings
Type
article
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article

Parameter optimization of Mg reduction by thermo-silicon method using Taguchi method, grey relational analysis and preference selection index

Vu Viet Quyen
Materials Research Express
Surface Treatment and Coatings
article

Parameter optimization of Mg reduction by thermo-silicon method using Taguchi method, grey relational analysis and preference selection index

Vu Viet Quyen
article en

Abstract

Abstract This study used Taguchi L16 design to optimize four key variables including reduction temperature, Fe-Si molar ratio, CaF 2 content, and pelletizing pressure for the production of magnesium from Vietnamese dolomite via the silicothermal process. Performance was evaluated by reduction efficiency, product magnesium purity, and ferrosilicon utilisation ratio. Experimental data were analysed using Taguchi-Grey Relational Analysis with Principal Component Analysis and Preference Selection Index. Grey Relational Analysis method determined that the reduction temperature of 1250 °C, Fe-Si molar ratio of 1.3, CaF 2 ratio of 4% and pelletizing force of 120 MPa were optimal, while the Preference Selection Index method suggested a reduction temperature of 1300 °C, Fe-Si molar ratio of 1.3, CaF 2 ratio of 5% and pelletizing force of 80 MPa. Both methods agree that reduction temperature has the greatest effect on yield, with Fe-Si and CaF 2 ratios having a moderate effect and pelletizing pressure having a negligible effect at high reduction temperatures. An Fe-Si ratio of 1.3 consistently production efficiency and reducing agent costs. The results demonstrates the efficacy of multi-criteria decision-making techniques in refining complex metallurgical processes and elucidates the interdependencies among operating parameters, offering actionable insights to enhance magnesium yield and ferrosilicon efficiency.

Materials Research ExpressVol. 12(7)
Openalex Percentile: Top 85%
Surface Treatment and Coatings
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