TY - GEN
T1 - Adaptive Neuro-Fuzzy Inference System (ANFIS) Method to Optimize the Reduction Process of Saprolite Ore Composites in Tube Furnace
AU - Surjandari, Isti
AU - Puspita, Angella Natalia Ghea
AU - Zulkarnain, Zulkarnain
AU - Kawigraha, Adji
AU - Permatasari, Nur Vita
AU - Rus, Annisa Marlin Masbar
PY - 2019/7
Y1 - 2019/7
N2 - According to Indonesia Mineral and Coal Law No. 1 in 2014 about the Enhancement of Mineral Value-Added, it is necessary for mining company to process and refine nickel ore domestically to increase its value. In this paper, value of nickel ore is increased by producing a saprolite ore composite which is a mixture of a certain amount of saprolite, coal, sulfate, and bentonite. Then a reduction process of the composite using pyrometallurgical method is designed to find the best combination of the coal ratio, process temperature, process time, and the ratio of additive (Na2SO4) towards the availability of carbon along with processing time and temperature as the primary concern. Then the chemical composition of the saprolite ore composites are analyzed, especially nickel, using X-Ray-Difference Fluorescence (XRF). In order to find the best combination, Adaptive Neuro-Fuzzy Inference System (ANFIS) method is employed to analyze the XRF result due to its ability to reduce the dimension of search space by distributing input information over the network. The objective of this research is to obtain optimal factor combination for reduction process of saprolite ore composites in Tube Furnace by looking at the results of the chemical compositions of Ni which was tested through XRF using ANFIS method. The optimal factor combination is ratio coal 15% with a type of additive Ca2SO4or Composite SB15Ca10P2with temperature 1200 °C and process time 3 hours.
AB - According to Indonesia Mineral and Coal Law No. 1 in 2014 about the Enhancement of Mineral Value-Added, it is necessary for mining company to process and refine nickel ore domestically to increase its value. In this paper, value of nickel ore is increased by producing a saprolite ore composite which is a mixture of a certain amount of saprolite, coal, sulfate, and bentonite. Then a reduction process of the composite using pyrometallurgical method is designed to find the best combination of the coal ratio, process temperature, process time, and the ratio of additive (Na2SO4) towards the availability of carbon along with processing time and temperature as the primary concern. Then the chemical composition of the saprolite ore composites are analyzed, especially nickel, using X-Ray-Difference Fluorescence (XRF). In order to find the best combination, Adaptive Neuro-Fuzzy Inference System (ANFIS) method is employed to analyze the XRF result due to its ability to reduce the dimension of search space by distributing input information over the network. The objective of this research is to obtain optimal factor combination for reduction process of saprolite ore composites in Tube Furnace by looking at the results of the chemical compositions of Ni which was tested through XRF using ANFIS method. The optimal factor combination is ratio coal 15% with a type of additive Ca2SO4or Composite SB15Ca10P2with temperature 1200 °C and process time 3 hours.
KW - Adaptive Neuro-Fuzzy Inference System (ANFIS) method
KW - Optimization
KW - Reduction process
KW - Saprolite ore
UR - http://www.scopus.com/inward/record.url?scp=85074891844&partnerID=8YFLogxK
U2 - 10.1109/ICSSSM.2019.8887655
DO - 10.1109/ICSSSM.2019.8887655
M3 - Conference contribution
T3 - 2019 16th International Conference on Service Systems and Service Management, ICSSSM 2019
BT - 2019 16th International Conference on Service Systems and Service Management, ICSSSM 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th International Conference on Service Systems and Service Management, ICSSSM 2019
Y2 - 13 July 2019 through 15 July 2019
ER -