Title: Implementation Of Machine Learning For Monitoring And Controlling Glass Quality In The Production Process
Authors: Arsenio Rafi, Sumardi
Volume: 9
Issue: 3
Pages: 74-79
Publication Date: 2025/03/28
Abstract:
In the glass industry, Quality Control (QC) plays a crucial role in ensuring product quality. The Defect Detector system is a solution to enhance the efficiency and accuracy of Quality Control. With the Defect Detector, the QC process becomes faster and more accurate, reducing raw material wastage and enhancing customer satisfaction. Additionally, the use of the defect detector tool can detect defects far more extensively, with an estimated 5 times the detection rate of humans. The implementation results of this system can accurately pinpoint defects, even ones that are invisible to the human eye without assistance tools, thus improving the quality of glass quality control.