Artigos
URI permanente para esta coleçãohttps://rigalileo.itegam.org.br/handle/123456789/5
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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 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 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 LeiteThis 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.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 dos; ALENCAR, David Barbosa de; CAMPOS, Paola Souto; MORAES, Nadine Mustafa; Jandecy Cabral LeiteThis 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.Item Desenvolvimento de um Dispositivo Inteligente de Monitoramento de Energia Elétrica Integrado à Plataforma SGE com Aplicação da Lógica Fuzzy para Tomada de Decisão na Gestão Energética da Indústria 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SANTOS JUNIOR, Hélio Andrade dos; ALENCAR, David Barbosa de; SANTOS, Eliton Smith dos; CAMPOS, Paola Souto; MORAES, Nadime Mustafa; SANCHES, Antônio Estanislau; LEITE, Jandecy CabralEfficient management of electrical energy in industrial environments is a crucial challenge, exacerbated by the continuous increase in consumption and frequent inefficiencies in resource utilization. In this context, Industry 4.0 and Smart Grids emerge as promising approaches, integrating advanced digital technologies to optimize energy production, distribution, and consumption. This study developed and validated a portable electrical energy monitoring device integrated into the SGE platform, applying fuzzy logic to support real-time decision-making. The device demonstrated the ability to conduct detailed analyses of energy consumption and efficiency, enhancing the accuracy in detecting losses and critical inefficiency points.Item Sistema Ciber-Físico na Indústria 4.0 - Aplicado em Testes de Rigidez Dielétrica em Unidades Evaporadoras de Aparelhos de Ar-Condicionado(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) ALENCAR, Wanderson Grey Rodrigues de; ALENCAR, David Barbosa de; SANTOS, Eliton Smith dos; CAMPOS, Paola Souto; MORAES, Nadime Mustafa; SANCHES, Antônio Estanislau; LEITE, Jandecy CabralCyber-physical systems (CPS) play a central role in the digital transformation of Industry 4.0, especially in industrial sectors such as HVAC (heating, ventilation, and air conditioning). This study presents the application of CPS in dielectric strength testing of air conditioning evaporator units, essential for ensuring equipment safety and efficiency. The main objective was to develop an automated control system integrating CPS to monitor and optimize these tests, overcoming the limitations of traditional methods. The proposed system demonstrated significant improvements in accuracy, safety, efficiency, and traceability.Item Aplicação de Controle Fuzzy em Microgrids Solares como Auxílio na Mitigação de Interrupções em Comunidades Isoladas no Amazonas à Portaria Nº 140/2022(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SILVA NETO, Oswaldo Wanderley da; ALENCAR, David Barbosa de; SANTOS, Eliton Smith dos; BRITO JÚNIOR, Jorge de Almeida; SANCHES, Antonio Estanislau; LEITE, Jandecy CabralIsolated communities in the Amazon face significant challenges in accessing reliable energy due to logistical difficulties and lack of infrastructure. Photovoltaic microgrids emerge as a viable alternative but suffer from instability and frequent interruptions caused by environmental variability. This study investigates the implementation of fuzzy control in these systems to mitigate supply failures and improve operational efficiency, in compliance with INMETRO's Portaria No. 140/2022. The results show that fuzzy control is a promising solution to enhance the reliability and sustainability of energy in isolated communities.Item Aplicação da lógica Fuzzy na emissão de notas fiscais em processos administrativos na Indústria Lean Office 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SOARES, Vera Alana Nobre; ALENCAR, David Barbosa de; SANTOS, Eliton Smith dos; CAMPOS, Paola Souto; MORAES, Nadime Mustafa; LEITE, Jandecy CabralIndustry 4.0 has brought the need to integrate advanced technologies to improve the efficiency and agility of administrative processes. This study proposes the application of fuzzy logic to optimize the issuance of invoices, a critical process that faces challenges such as manual errors, delays, and high costs. A fuzzy model was developed that identifies key variables, applies inference rules, and tests the solution in a real environment with operational data. The results indicate a significant reduction in errors and processing times, in addition to gains in tax compliance and customer satisfaction.Item Digital Technologies Review for Manufacturing Processes(Instituto de Tecnologia e Educação Galileo da Amazônia, 2022) PARENTE, Ricardo Silva SILVA, Italo Rodrigo Soares SIQUEIRA JUNIOR, Paulo Oliveira UHLMANN, Iracyanne Retto; LEITE, Jandecy CabralThe industrial processes transformation caused by Industry 4.0 is advancing in countries like China, Japan, Germany, and the United States. However, developing countries such as Brazil still face challenges in adapting to the digital era. This study presents a review of the main technologies used in smart manufacturing and the challenges of its implementation in Brazil. The research was based on 114 articles and two books collected from the Web of Science database. The results indicate that the primary challenges for Industry 4.0 adoption in Brazil include poor technological infrastructure, lack of investment in technology, and insufficient training of qualified professionals. Although the study focuses on the Brazilian scenario, its conclusions are applicable to other emerging countries, providing a general overview of concepts and practical applications developed by the international academic community.Item Application of Deep Neural Network in Intelligent System with Production Dashboard(Instituto de Tecnologia e Educação Galileo da Amazônia, 2022) RAMOS JUNIOR, Juarez da Silva LEITE, Jandecy Cabral GOMES, Marivan Silva PAULA, Railma Lima de CARVALHO, Michael da Silva SILVA, Ítalo Rodrigo Soares SIQUEIRA JUNIOR, Paulo Oliveira PARENTE, Ricardo Silva MIRANDA, Luís Gabryel dos Santos; LEITE, Jandecy CabralThe Lean Manufacturing process is a strategic methodology aimed at reducing production waste, ensuring product quality, minimizing delivery time, and reducing defects. However, the company analyzed lacks technologies that enable the effective implementation of this methodology. This study proposes the development of an Intelligent Lean Manufacturing System based on the requirements of a Manufacturing Execution System (MES), assisting decision-making in production control and management through technologies such as Artificial Intelligence, Internet of Things (IoT), and Embedded Systems. The system includes Deep Neural Network (DNN) algorithms to forecast demand, optimize processes, and monitor real-time indicators. The research demonstrates that the application of these technologies can reduce costs and improve production quality, raising manufacturing maturity levels to Industry 4.0 standards.