Optimization saprolite ore in tube furnace with support vector machine (SVM)
Penulis:Â Puspita, Angella Natalia Ghea;Â Kawigraha, Adji;Â Permatasari, Nur Vita;Â Respatid, Santi Ari
Informasi
JurnalAIP Conference Proceedings
PenerbitAmerican Institute of Physics Inc.
Volume & EdisiVol. 2538
Halaman -
Tahun Publikasi2023
ISSN0094243X
ISBN978-073544466-9
Jenis SumberScopus
Abstrak
The laterite nickel ore is generally divided into 2 types of ore, namely limonite ore, which content a large Fe and small Ni and saprolite ore which content small Fe and large Ni. Indonesia holds 23.7% of world nickel laterite resources, with total more than 9 billion wet metric tons. To increase the added value of nickel ore, it is necessary to process/refine nickel ore through Pyro metallurgy and Hydrometallurgy technique. This research uses pyro metallurgy technique to increase added value of the saprolite ore with reduction process in Tube Furnace. Reduction process has several factors that influence the reduction process that are coal ratio, process temperature, process time, and the ratio of additive. The several factors serve as parameter to get the most optimal factor combinations. The reduction process using composite which is mixing of saprolite ore, coal, additive and bentonite with certain percentage. After the reduction process in Tube Furnace, the results analysis using X Ray-Difference Fluorescence (XRF) to know the chemical composition. The objective of this research is to obtain the optimal factor combination for the reduction process of saprolite ore composite in Tube Furnace by looking at the results of the chemical composition of Ni which was tested through XRF using Support Vector Machine (SVM) method. SVM method is one of the most effective methods of optimization, based on statistical theory which is a new class model that can be used to predict of the value. The optimal factor combination is composite SB27Ca10P2 or percentage coal ratio 27%, type of additive Ca2SO4 in temperature 1300 0C and process time 3 hours. © 2023 Author(s).
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