Otomotiv Üretim Hatlarindaki 3D Parçalarin Kalite Kontrolü Için Endüstri 4.0 Ile Uyumlu Yapay Görme Sisteminin Geliştirilmesi

Abstract

Image processing technology is a technology that is increasingly used in almost all sectors and continues to develop today. When its usage areas are examined, it is frequently used in mold design and manufacturing, metal part production, and quality control applications after sheet metal forming. The most important advantages of image processing technology are that it reduces human labor, has a low error rate, and accelerates the processing time in the area where it is used. In this study, a machine vision system compatible with Industry 4.0 has been developed for the quality control of 3D parts in automotive production lines. An image processing-based quality control system, which is compatible with Industry 4.0, is designed with a high control sensitivity compared to existing methods, low processing time, and error detection of post-production parts, various metric measurements. The designed system consists of two main parts, the control software, and the image acquisition cabinet. First, the raw image taken in the image acquisition cabinet with appropriate lighting was transferred to the image processing software and then all the measurement results were obtained. Image processing software was performed with LabVIEW Vision Builder AI (Automated Inspection) program. A suitable software infrastructure was created for the parts by performing pixel-based measurements and morphological operations on the image. When the results obtained are examined, it is seen that error detection and measurement processes can be performed with an error rate of less than 0.04%. © 2022 IEEE.