Mapeamento de rotas para manufatura aditiva por deposição a arco utilizando processamento de imagens

• Ano de defesa: 2023
• Autor(a) principal: Chipanski, Matheus Antunes
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Curitiba; Brasil; Programa de Pós-Graduação em Engenharia Elétrica e Informática Industrial; UTFPR
• Palavras-chave em Português: Manufatura aditiva; Processamento de imagens; Processos de fabricação - Planejamento; Algorítmos computacionais; Imagens digitais; Additive manufacturing; Image processing; Manufacturing processes - Planning; Computer algorithms; Digital images; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO; Engenharia Elétrica
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/31040

The advancement of additive manufacturing has enabled the creation of various technologies and manufacturing processes capable of working with various materials and applications in virtually all sectors of the industry. Among them, the wira and arc additive manufacture (WAAM) has aroused in recent years great interest in the productive and academic environment because it is considered promising for the manufacture of metal parts with medium and large sizes. This technology has unique characteristics related to the planning of material deposition that are important for the quality of the parts produced, details such as thin walls, areas with large mass, internal fill bottlenecks, and contours need to be addressed differently in process planning. This work proposes a mapping of the regions of interest to this technology through the decomposition of binary digital images extracted from 3D models, focusing on the recognition of these areas. The project uses image processing algorithms, computational geometry and graph theory to recognize areas of interest and uses this classification to generate a material deposition route specific to each image region. The algorithm was implemented in Python language for proof of concept and several tests with various geometries are presented. Print tests to verify the routes generated were performed with a low-cost polymer filament printer. The results show that the proposed algorithm was able to map the main areas of interest, including the possibility of the user to influence the mapping.