Logistic Regression Based Conveyor Control for Material Handling Process

Increasing efficiency and reducing human errors are two crucial steps in automation for all sectors of industry. In industries, the job pieces of various size will be moved on the same belt. This must be separated in various locations within the manufacturing line. Once the products are produced, they must move automatically on to the conveyor belts. The work pieces of different sizes will be detected by the sensors that are stored in different locations. This system ensures the quality and quantity of the product being conveyed from one system to another. Conveyors that produce one type of object or product can monitor only one product at a time. If more products need to be monitored, a new system should be developed. Wireless control of the machine plays a very important role that's to scale back the manual work and save funds for the enterprise. It can reduce and conserve energy and power by automatically turning on and off the belt using sensors. The precision is often improved if these sensors are controlled by machine learning based algorithm. The proposed method offers accurate result to the belt. Test result shows that the energy saved is 13% higher than the conventional method.