PPG.EGPSA/ITEGAM

URI permanente desta comunidadehttps://rigalileo.itegam.org.br/handle/123456789/1

A comunidade dispõe da produção técnica e científica do Programa de Pós-graduação em Engenharia, Gestão de Processos, Sistema e Ambiental (PPG.EGPSA) do Instituto de Tecnologia e Educação Galileo da Amazônia (ITEGAM), fruto da atividade de pesquisa e desenvolvimento (P&D). É possível acessar os trabalhos de conclusão do programa de pós-graduação, artigos e livros vinculados a pesquisa, desenvolvimento, inovação e extensão.

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Assunto: search.filters.subject.Ciências Exatas e da Terra

Resultados da Pesquisa

Agora exibindo 1 - 5 de 5
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    Desenvolvimento de método para obtenção de trilhas condutivas com grafeno por esfoliação em fase líquida aplicadas à eletrônica impressa na Indústria 4.0
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) VALADÃO, Suélem Cabral; LEITE, Jandecy Cabral
    This study presents the development and characterization of conductive tracks based on graphene obtained via liquid-phase exfoliation (LPE), applied to printed circuit boards (PCBs) on FR4 substrates. Graphene synthesis was carried out by dispersing graphite flakes in a surfactant-assisted solvent, followed by ultrasonic exfoliation for 30 minutes. The resulting material was characterized using XRD, SEM, and Raman spectroscopy, confirming the presence of multilayer graphene with moderate structural defects. Conductive inks were formulated with different proportions of Jutaicica resin, a natural Amazonian binder, achieving good adhesion to the substrate. Tests indicated average track thickness of ~72 µm and electrical conductivity of 0.75 and 0.91 (Ω.cm)-¹ for inks 1 and 2, respectively. The findings demonstrate the potential of LPE graphene combined with Amazonian biodiversity inputs for the formulation of functional and sustainable conductive inks, aligned with sustainability principles and Industry 4.0.
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    Desenvolvimento de um sistema de monitoramento inteligente para determinação do ponto ótimo para o abate de animais de produção utilizando visão computacional e inteligência artificia
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) FARIAS, Djalma Farias e; NASCIMENTO, Manoel Henrique Reis
    Beef cattle production faces challenges in accurately identifying the ideal slaughter time for Nelore cattle, affecting yield and animal welfare. Traditional monitoring methods, such as manual weighing and visual inspection, may compromise meat quality and increase costs. This study developed an intelligent monitoring system using computer vision and artificial intelligence to determine the optimal slaughter moment for Nelore cattle. The system applies deep learning algorithms and video cameras to analyze animals in real time, considering productive and morphological parameters. A cost-benefit analysis was performed based on hardware, software, and operational returns. Results showed increased productivity, improved slaughter precision, and an estimated 268.42% ROI over five years, demonstrating the technical and economic feasibility of AI-based livestock monitoring.
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    Algoritmo Genéticos aplicado à Qualidade de Energia - DASHBOARD
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) ALMEIDA, Anderson Alexandre Silva de; LEITE, Jandecy Cabral
    Registration of a computer program entitled "Genetic Algorithms Applied to Power Quality - DASHBOARD," valid for 50 years from January 1st following the publication date (12/17/2024). The program was created for specific applications outlined in the technical areas defined by the National Institute of Industrial Property (INPI).
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    Sistema de Teste Funcional com Rastreabilidade para Carregadores de Celular
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) MAUÉS, Elvis Jardim; LEITE, Jandecy Cabral
    Registration of a computer program entitled "Functional Test System with Traceability for Cell Phone Chargers," valid for 50 years from January 1st following the publication date (11/14/2024). Developed in C++, the program applies to specific areas defined by the National Institute of Industrial Property (INPI).
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    Redes Neurais Artificiais para Comparação entre Propriedades Mecânicas Materiais
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) DIAS, Jonathan Oliveira; LEITE, Jandecy Cabral
    Registration of a computer program entitled "Artificial Neural Networks for Comparison of Mechanical Properties of Materials," developed in Python. The program is valid for 50 years from January 1st following the publication date (12/03/2024). Its applications cover engineering, materials, and artificial intelligence areas as specified by the National Institute of Industrial Property (INPI).