G-OPTIMAL DESIGN OF NON-LINEAR MODEL TO INCREASE PURITY LEVELS OF SILICON DIOXIDE

Abstract

Silicon Dioxide (SiO2) is one of the most abundant minerals found on earth. SiO2 is widely used in various fields, so its availability as a finite natural resource diminishes. A purity procedure can raise the purity of low-quality silica by altering the temperature and rate of temperature rise. This study aims to obtain the best design for increasing SiO2 levels—the G-optimal design on a non-linear model using the Variable Neighborhood Search (VNS) algorithm. The VNS algorithm employs two types of neighborhoods, one acquired by replacing one design point with a candidate set and the other by replacing two design points with two points in the candidate set. The model used to increase silicon dioxide's purity is a non-linear model that follows the exponential decay distribution. The best design points obtained from the G-optimal design on the relationship between temperature (oC) and the rate of temperature increase (oC/min) 800 oC to 900 oC is a pair of points 800 oC and 1,67 oC /min, 800 oC and 2,17 oC/min, 815 oC and 2,50 oC/min, 825 oC and 2,00 oC/min, 845 oC and 2,34 oC/min, 895 oC and 3,34 oC/min 900 oC and 3,50 oC/min with a G-efficiency of 96,41%.