Application of machine vision technology in defect detection of high-performance phase noise measurement chips

Abstract

The problem of chip defects has always existed in industrial production, and since there are more and more environmental problems caused by chip defects, people have attached greater importance to the identification and detection of chip defects. Pursuant to the ecological environmental problems caused by chip defects in the process of chip production, this paper uses machine vision technology to detect the defects of high-performance phase noise measurement chips. The results suggest that the accuracy of machine vision technology for the identification of chip defects reaches up to 98%. The production volume of organic waste gas decreases from 5968.0t/a to 4000t/a. The yield of organic wastewater decreases from 5496m3/d to 4600m3/d. The production amount of solid waste reduces from 8000t/a to 6500t/a. The aforementioned data all confirm that machine vision technology has the advantages of automation, high detection efficiency, and high accuracy of defect identification for the defect detection of high-performance phase noise measurement chips. And also, by improving the chip defects, the discharge volume of waste gas, wastewater, and solid waste in the chip production process is reduced, and thereupon the ecological environment is ameliorated.