Brief description

The paper presents an educational intelligent system “Expert Polymer” for identifying particles appropriate for 3D printing. The software system is designed to analyze images of polymer materials at manufacturing site via optics. It is planned that this intellectual system will be used as a training software package for students in higher educational institutions, as well as for bioengineers and materials scientists for research and production purposes. The study used Internet of Things (IoT) technologies to obtain images from optical measuring devices (electron microscope, etc.) from the system users and send them the results of image analysis. By the interaction of an electron microscope with the created software system, the task was performed to determine the number of all particles and the number of particles satisfying the 3D printing algorithm. Based on these data, the expert decides on the possibility of using polymer particles for subsequent 3D printing. To implement the system, modern libraries of the Python programming language were used, namely Pandas, Direction2 and YOLOv5 and others.