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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Resultados da Pesquisa

Agora exibindo 1 - 10 de 78
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    Automation and Intelligent Control in Drying and Curing of Paints and Varnishes: Application of Industry 4.0
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SOUZA, Raimundo Alberto Farias de; SANTOS, Eliton Smith dos
    This study investigates the technologies, methods and challenges involved in drying and curing paints and varnishes applied to reflective strips, with emphasis on Industry 4.0-based solutions. It proposes an integrated hardware–software model for automatic detection of curing level through light radiation. A controlled-environment prototype and real-time control system aim to optimize the process, accelerate UV photopolymerization and improve product quality.
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    Análise dos Desafios na Transição para Indústria 4.0: um Estudo Sobre a Integração de Sistemas de Custeio em Ambientes Automatizados
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SILVA, Maeli Oliveira da; MARINELLI FILHO, Nelson
    This paper analyzes the challenges faced during the transition from traditional costing systems to absorption costing systems in the context of Industry 4.0. Through the analysis of heat maps applied to an industrial costing spreadsheet for electronic components, the study identifies and categorizes inconsistencies that reflect broader structural challenges of industrial digital transformation. The methodology was based on the application of data visualization techniques to identify null and zero values at different stages of the migration process. The results reveal seven critical categories of inconsistencies: interoperability issues, complexity in the allocation of indirect costs, implementation and maintenance costs, workforce training, real-time data management, compliance and security, and adaptation to the dynamics of Industry 4.0. It was concluded that such inconsistencies represent significant barriers to a successful transition, especially in industries with a high degree of automation. The study proposes a framework for assessing and mitigating these challenges, contributing to the literature on digital transformation in the Brazilian industrial context.
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    Técnicas da Indústria 4.0 aplicadas na melhoria do processo de corte dos terminais das baterias de íon-Lítio
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) MACIEL, Lincoln Fabio Luiz; NASCIMENTO, Manoel Henrique Reis; ALENCAR, David Barbosa de
    Software registration using Industry 4.0 techniques to improve the terminal cutting process in lithium-ion batteries, developed in C++ and focused on industrial applications in areas AD-06, IN-01, and IN-05.
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    Aplicação de Inferência Fuzzy Para Tomada de Decisão em Processos de SMT
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) LEITE, Herbety Lima; NASCIMENTO, Manoel Henrique Reis; ALENCAR, David Barbosa de; BRITO JUNIOR, Jorge de Almeida
    Software developed in Python applying fuzzy inference for decision-making processes in SMT (Surface-Mount Technology), targeting industrial process optimization. The registration is recognized under Brazilian intellectual property law and categorized within engineering and automation domains.
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    Sistema Inteligente para monitoramento de subestações elétricas integrado à plataforma SGE: uma aplicação da Indústria 4.0
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SANTOS JUNIOR, Hélio Andrade dos; NASCIMENTO, Manoel Henrique Reis; ALENCAR, David Barbosa de
    Python-based software developed for intelligent monitoring of electrical substations. Integrated with the SGE platform, it provides functionalities tailored for Industry 4.0 applications, enabling automation, real-time data acquisition, and remote diagnostics of critical infrastructure. Classified under electrical engineering and industrial automation.
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    Sistema inteligente para detecção de falhas utilizando algoritmo de Árvore de Decisão
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) PENEDO, Jorge Eduardo Santos; PALADINI, Edson Pacheco; SILVA, Carlos Américo de Souza; LEITE, Jandecy Cabral
    Python-based software employing Decision Tree algorithms to detect faults in industrial or computational systems. Designed for Industry 4.0 environments, it aims to enhance operational reliability and enable automated diagnostics.
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    Sistema inteligente para detecção de falhas utilizando algoritmo de máquina de vetores de suporte – SVM
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SILVA, Carlos Américo de Souza; PALADINI, Edson Pacheco; PENEDO, Jorge Eduardo Santos; LEITE, Jandecy Cabral
    Python-based software using Support Vector Machine (SVM) algorithms for fault detection systems. Aimed at intelligent automation in industrial settings, the software enhances predictive decision-making accuracy in the context of Industry 4.0.
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    Sistema inteligente para classificação de falhas na manufatura de placas utilizando algoritmo de Machine Learning KNN
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) PENEDO, Jorge Eduardo Santos; PALADINI, Edson Pacheco; SILVA, Carlos Américo de Souza; LEITE, Jandecy Cabral
    Python-based software using the K-Nearest Neighbors (KNN) machine learning algorithm to classify failures in PCB manufacturing lines. Designed for Industry 4.0 environments, it aims to improve predictive failure detection accuracy in automated industrial contexts.
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    Análise dos Desafios na Transição para Indústria 4.0: Um Estudo Sobre a Integração de Sistemas de Custeio em Ambientes Automatizados
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SILVA, Maeli Oliveira da; FILHO, Nelson Marinelli; GUIMARÃES, Gil Eduardo; LEITE, Jandecy Cabral; FERREIRA, Matheus Rissardi; Jandecy Cabral Leite
    This paper analyzes the challenges faced during the transition from traditional costing systems to absorption costing systems in the context of Industry 4.0. Through the analysis of heat maps applied to an industrial costing spreadsheet for electronic components, the study identifies and categorizes inconsistencies that reflect broader structural challenges of industrial digital transformation. The results reveal seven critical categories of inconsistencies: interoperability issues, complexity in the allocation of indirect costs, implementation and maintenance costs, workforce training, real-time data management, compliance and security, and adaptation to the dynamics of Industry 4.0. It was concluded that such inconsistencies represent significant barriers to a successful transition, especially in industries with a high degree of automation.
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    Automation and Intelligent Control in Drying and Curing of Paints and Varnishes: Application of Industry 4.0
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SOUZA, Raimundo Alberto Farias de; SANTOS, Eliton Smith dos; ALENCAR, David Barbosa de; CAMPOS, Paola Souto; MORAES, Nadine Mustafa; Jandecy Cabral Leite
    This research aims to investigate the technologies, methods, and challenges in the drying and curing process of paints and varnishes applied to reflective strips, focusing on implementing Industry 4.0-based solutions. It proposes an integrated hardware and software model to automatically detect the curing level through light radiation, along with a real-time control system to optimize the process. Among the evaluated technologies, ultraviolet light curing (photopolymerization) stands out, aiming to enhance industrial production with quality and efficiency.