Abstract
This paper considers the task of creating a prototype of the expert system “Expert-Polymer”, designed to help a bioengineer identify particles of polystyrene-based polymers suitable for 3D printing by selective laser sintering (SLS). To implement the software product, an overview study of the properties of polystyrene particles used in 3D printing was performed. When designing the expert system, some properties of polystyrene-based polymer particles were determined, based on which the system derived recommendations on their suitability for 3D printing by the SLS method. The expert system was implemented using the Python programming language using the Detectron2 library for segmenting polymer particles in an image, as well as the OpenCV computer vision library for image analysis, classification, and processing. As a result, a prototype of an expert system for the detection of polymer particles for 3D printing was developed with an analysis of the important properties of polymer particles that affect the quality of SLS 3D printing. This paper provides a full report on the development of an expert system for the detection and analysis of polymer particles.
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