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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459 resultados
Resultados da Pesquisa
Item Ozonização como processo de desinfecção da água para consumo humano: eficiência e sustentabilidade(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) FERREIRA, Arthur Joaquim de Araújo; RODRIGUES, Fábio; SILVA, Simone daWater disinfection is essential to eliminate pathogenic microorganisms and ensure sanitary safety. Among emerging technologies, ozonation stands out due to its high efficiency and environmental sustainability. This study analyzes the effectiveness of ozone application in water disinfection in Itajaí/SC, addressing its physicochemical principles, technical-economic feasibility, and environmental impacts. The methodology combined literature review, experimentation, and case study, showing that ozonation is more effective than chlorine, especially against resistant pathogens, and reduces toxic byproducts while providing synergistic effects when combined with other methods. It concludes that ozonation is a viable and sustainable alternative for sanitation, contributing to the improvement of drinking water quality.Item 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 dosThis 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.Item Proposta de Implantação da Tributação Ambiental como Ferramenta de Incentivo na Conservação e Desenvolvimento Sustentável: um Estudo de Caso sobre Potencialidade do IPTU Verde na Cidade de Manaus(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) MONTEIRO, Ciro Allister Reis; LEITE, Jandecy CabralThis work reflects on the implementation of the Green IPTU as a public policy instrument to promote environmental conservation and sustainable development in the city of Manaus. Using a qualitative and quantitative approach, a case study is conducted based on Bill No. 248/2013, which proposes partial tax exemption for properties that adopt sustainable practices. The research discusses the legal, economic, and socio-environmental feasibility of environmental taxation, with emphasis on the polluter-pays principle and the socio-environmental function of urban property, as established in the Federal Constitution. It analyzes aspects such as the impact of tax exemptions on municipal revenue, public awareness, and the criteria for adherence to the benefit. The study contributes to the debate on environmental public policies in the Amazonian urban context, highlighting the role of taxation as an extrafiscal instrument capable of inducing sustainable behaviors and mitigating environmental damage in citiesItem 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, NelsonThis 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.Item 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 deSoftware 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.Item 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 AlmeidaSoftware 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.Item 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 dePython-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.Item 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 CabralPython-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.Item 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 CabralPython-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.Item 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 CabralPython-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.