A Model for Quality Management in Industrial Products Based on Machine Learning and Image Processing Techniques

Products are typically mass produced in industries. Anytime mass production is involved, it presents a number of difficulties, including problems with efficiency, costs, and time consumption. Automation has been used by numerous industries as a solution to these issues. A system that checks the finished goods for flaws at the end of the production line is necessary to preserve the quality of the items. To deal with the aforementioned issues, the majority sectors of industries have started using automated systems employing image-based processing technique. An image-based processing system is one of the major components in industrial automation production operations which has high rate of effectiveness due to the availability of modernized digital cameras and various communication interfaces. Manufacturers place the highest attention on ensuring quality. Component identification during manufacturing flow must be possible with machines that can use computer vision effectively. In this paper, we present an industrial image-based processing quality management system.