Recently, there are much need to automate boring and repetitive jobs. Industrial automation is becoming more and more adaptable to modern technological developments. This work presents an experimental situation for controlling a DC motor used to drive a conveyor belt. This paper demonstrates the use of deep learning to facilitate task selection, placement, and object transfer using intelligent technology with advanced recognition methods. In this paper, the design, implementation, and control of the smart production line is studied. A small prototype of a real production line is built to meet the customer's demand or factory needs such as (auto assembly, packaging plants, etc...). This paper includes the required calculations, design, control system, and manufacturing process for the entire system. We will be able to (make operations on things easier, increase sorting accuracy, reduce the cause of operator injuries, increase work efficiency, increase production capacity, reduce time, workspace and labor cost, and manually and automatically control production lines.