Intelligent Quality Control System for Product Manufacturers through ML

One of the most important components in ensuring product quality before it reaches the market is industrial inspection. The visual system, including human vision, machine vision, or a mix of both, can be used to carry out the inspection tasks. In this research, we present a method that can regulate the product quality of press parts. Visual inspection systems are used to accomplish quality control by identifying acceptable parts from rejected goods. Complete quality control of the raw materials is a requirement for large-scale production enterprises. The primary goals are to create an image processing system that can assess a part's dimension and determine whether it should be accepted or rejected. Calculating the pixel value will yield the part's dimensions. The result shows its possibility to be used as automated visual inspection system.