Parameter optimization of Mg reduction by thermo-silicon method using Taguchi method, grey relational analysis and preference selection index
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, pr...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2025-01-01
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| Series: | Materials Research Express |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/2053-1591/ade931 |
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| Summary: | 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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| ISSN: | 2053-1591 |