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Development of an Educational Intelligent System to Detect Particles Suitable for 3D-Printing

Авторы

Burnashev R.A., Farahov R.R., Nasibullin I.A., Avdeeva A.A., Bolsunovskaya M.V., Enikeev А.I.
12th World Conference “Intelligent System for Industrial Automation” (WCIS-2022). WCIS 2022. Lecture Notes in Networks and Systems. 2024, vol 912. Springer, Cham.

Краткое описание

This report presents the educational intelligent system “Expert-Polymer” for identifying particles suitable for 3D printing. The problem has a direct practical application — it is necessary to optimize the resources spent in 3D printing to build some materials, and not print them if the materials (in this case, polymers) do not have properties suitable for their further exploitation. The complexity of this task lies in the fact that, based on unformalized data — images of polymer particles obtained from an electron microscope — it is necessary to determine the number of all particles and the number of particles that satisfy the 3D printing algorithm, and based on these data to make a decision on the possibility of using particles for 3D -print. Therefore, the next step is the integration of the educational system to optical measuring instruments (research instruments, electron microscope, etc.). The system can be used in the educational process of educational institutions.

Ключевые слова

This report presents the educational intelligent system “Expert-Polymer” for identifying particles suitable for 3D printing. The problem has a direct practical application — it is necessary to optimize the resources spent in 3D printing to build some materials, and not print them if the materials (in this case, polymers) do not have properties suitable for […]

Burnashev R.A., Farahov R.R., Nasibullin I.A., Avdeeva A.A., Bolsunovskaya M.V., Enikeev А.I. Development of an Educational Intelligent System to Detect Particles Suitable for 3D-Printing // 12th World Conference “Intelligent System for Industrial Automation” (WCIS-2022). WCIS 2022. Lecture Notes in Networks and Systems. 2024, vol 912. Springer, Cham. Pp. 84-95. https://doi.org/10.1007/978-3-031-53488-1_10.