Digital design and visualization system for 3D-printed capsules in agricultural production

The results of the development of an automated system for optimizing the parameters of 3D-printed capsules for crop production, ensuring minimal material consumption while meeting biological and strength requirements are presented in this paper. Methods of nonlinear programming (Sequential Least Squares Programming and Trust-Region Constrained) were used, integrated with the geometric and strength model of the structure. Tests were conducted on five plant types, demonstrating a reduction in material consumption by 12-24 % (average value 18.3 %), a decrease in design time from 30-60 minutes to 1 minute, algorithm convergence success rate of 96 %, and compliance with strength requirements in 100 % of cases. A visualization module was developed for comprehensive analysis of parameter evolution and economic effects. Conclusions: the system improves economic efficiency, reproducibility, and quality of designs; it is applicable in scientific, educational, farming, and industrial contexts, demonstrates the potential of digitization and precision agriculture, and establishes a foundation for further functionality expansion and adaptation to various agricultural engineering tasks.