AUTOMATION OF COST CALCULATION IN 3D PRINTING: ARCHITECTURAL SOLUTIONS AND ALGORITHMS FOR DIGITAL MODEL COMPLEXITY ANALYSIS
DOI:
https://doi.org/10.32782/mathematical-modelling/2026-9-1-23Keywords:
additive manufacturing, 3D printing, cost price, geometric descriptors, IoT monitoring, automation of calculationsAbstract
The properties of the schedule construction procedure, which formalizes the card method for manual scheduling, are considered A pressing scientific and practical problem of developing and implementing a comprehensive automated cost calculation system for additive manufacturing is examined and addressed. The current state of the 3D printing market is examined, revealing that existing cost estimation methods often ignore complex product geometries, leading to significant financial errors. The need for a transition from linear calculation models to an integrated approach combining digital model analysis and hardware monitoring is substantiated. Methods for geometric analysis of STL polygonal meshes are analyzed. The study identifies and systematizes key complexity descriptors, including polygon count, mesh density, surface area, and feature count. Algorithmic support is described for data-based prediction of equipment runtime and consumable volumes for support structures. The software implementation of the CalcMyPrint system, built on the principles of a monorepository using the Nx framework, has been detailed. The advantages of using a modern technology stack are identified: Angular 19 for creating a reactive interface, NestJS 11 for developing a scalable server-side component, and the Three.js library for providing interactive 3D visualization of models directly in a web browser. An innovative hardware solution is presented – a specialized IoT module based on a microcontroller and equipped with an optical encoder. A mechanism for precision filament consumption tracking is revealed, enabling real-time data on the actual length of filament used. Experiments have proven that direct measurement of material consumption is significantly more accurate than weighing, as it eliminates the influence of polymer hygroscopicity on calculation results. The developed assessment model was found to ensure high predictive accuracy in cost estimates, even for facilities with topological optimization and complex bionic designs. Implementing the system at enterprises has been shown to increase profitability by 15–25 % by automating inventory accounting, minimizing human error risks, and creating a transparent pricing system. Conclusions are drawn regarding the potential for integrating the system into the overall Industry 4.0 ecosystem.
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