Improving Technology for Creating Metal-Glass Systems Using Statistics and Machine Learning

The paper analyzes the results of the research conducted to obtain a metal-glass system by melting glass with a furnace and induction heating. Experiments and results are described to achieve the maximum tensile strength, maximum wear resistance and minimum fluidity of the metal-glass system under different glass melting methods. By using the SPC (Statistical Process Control) statistical method, a reliable analysis was made and objective conclusions were generated. An optimal regime for glass melting by induction heating of the metal-glass system was determined using machine learning.