Software para otimização do corte de materiais na indústria em geral.

Abstract

This work presented the development of a material cutting optimization system, a computational tool for industrial material cutting that incorporates algorithms for linear cutting (1D) and area cutting (2D), along with a graphical user interface featuring flexible and easily understandable constraint configuration. The material cutting optimization problem is fundamental in industry, directly impacting production costs and environmental sustainability through waste generation. The general objective of this work was to develop a complete cutting optimization system capable of supporting both types of cutting. The adopted methodology involved the implementation of exhaustive search algorithms with heuristics to overcome computational limitations, using dynamic programming and iterative generation of combinations for linear cutting (1D), and a modified bottom-left algorithm with automatic rotation support for bidimensional cutting (2D). The system was developed in Python with a graphical interface built using Python’s standard library, Tkinter, incorporating features for configuration, graphical visualization of the obtained results, and report exportation. Validation was carried out through six test scenarios presented throughout this work, three for linear cutting and three for bidimensional cutting, using simulated data with different configurations of materials and pieces to demonstrate the tool’s operation in different scenarios. The main results demonstrated the system’s ability to find efficient cutting solutions with efficiencies above 93% in all tested scenarios, processing problems with multiple types of pieces within viable processing times. The system showed the ability to reduce material waste compared to manual methods, while being adaptable to different industrial contexts. The main contribution of this work lies in the development of a complete and accessible tool that integrates multiple functionalities into a single platform, offering simultaneous support for both types of cutting and demonstrating the feasibility of heuristic approaches to overcome the computational limitations of highly complex problems.