Artigos
URI permanente para esta coleçãohttps://rigalileo.itegam.org.br/handle/123456789/5
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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 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 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 Transformação Digital no Polo Industrial de Manaus: Aumento da Eficiência na Produção de Baterias de Lítio através da Indústria 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) DAMASCENO, Alexandre Holanda; LEITE, Jandecy Cabral; BRITO JUNIOR, Jorge de Almeida; QUEIROZ JÚNIOR, Fernando Cardoso de; LEITE, Jandecy CabralThe lithium battery industry faces increasing challenges in terms of demand and expectations for sustainability and efficiency. In the context of the Manaus Industrial Hub, this study explores the application of Industry 4.0 technologies to overcome these challenges and increase production efficiency. The research implemented integrated cyber-physical systems, advanced automation, and real-time data analysis in a lithium battery assembly line, replacing manual processes with automated solutions. The results demonstrated significant improvements in production accuracy and speed, with a 40% reduction in cycle time and a 75% decrease in product rejection rates, highlighting the potential of digitalization to optimize industrial operations and meet the demands of a competitive global market. This study contributes to the literature on digital transformation in manufacturing, offering practical insights into the implementation of emerging technologies in complex industrial environments.Item Application of Automation and Computer Vision in Reducing Failures in the Production Process of Safety Belts(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) SOUZA, Kerlisson Silva de; SANTOS, Eliton Smith dos; ALENCAR, David Barbosa de; NASCIMENTO, Manoel Henrique Reis; SANTOS, Alyson de Jesus dos; LEITE, Jandecy CabralProduct quality is a key factor for companies to stand out in a highly competitive market. In the Manaus Industrial Hub (PIM), defect detection in safety belts is a crucial stage in the production process. This study proposes the automation of this process using computer vision and artificial intelligence (AI). The developed system captures images of the parts and applies Deep Learning techniques to identify defects. The results demonstrated 100% accuracy in defect detection, indicating that the proposed solution is effective in improving reliability and reducing waste in the manufacturing of safety belts.Item Otimização de Processos Industriais no Polo Industrial de Manaus (PIM): Desenvolvimento de um Dispositivo para Eliminar Contato Manual, Reduzir Esforço Repetitivo e Riscos Ergonômicos, Melhorando a Qualidade e Reduzindo Custos(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) CRUZ, Cristovão Santiago da; GUIMARÃES, Gil Eduardo; MARINELLI FILHO, Nelson; CORREA, Geraldo Nunes; TREVISOL, Janyel.; LEITE, Jandecy CabralThis study presents the development and implementation of an automated device for assembling steel balls and applying grease to column tubes in motorcycle production lines. The objective was to eliminate manual contact, promote ergonomic improvements, and optimize the production cycle. The methodology included requirements analysis, prototyping, pilot testing, and validation in a real environment. The results demonstrated a 25% reduction in cycle time, a 40% increase in product quality, and significant improvements in ergonomic indices. The economic analysis showed a financial return in less than 12 months. This work highlights the benefits of automation and suggests expanding the device to other stages of the production process, integrating advanced technologies such as artificial intelligence and cyber-physical systems to enhance efficiency and quality gains.Item Estudo de Caracterização da Eficiência Produtiva nas Indústrias de Montagem de Eletroeletrônicas do Polo Industrial de Manaus por Meio do Cálculo do OEE - Caso de Estudo de Automação(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) MONTEIRO, Isabela Zanotto; MARINELLI FILHO, Nelson; GUIMARÃES, Gil Eduardo; CORREA, Geraldo Nunes; FERREIRA, Matheus Rissardi; MARINELLI FILHO, NelsonThis study presents the implementation of Industry 4.0 enabling technologies, with an emphasis on the use of Digital Twins and the automation of OEE (Overall Equipment Effectiveness) calculation, applied to an electro-electronic assembly line at the Manaus Industrial Pole (PIM). The objective was to develop a solution capable of identifying, in real time, the times and reasons for production stoppages, aiming to optimize industrial processes and reduce operational costs. Data were collected through IoT sensors installed on production lines, integrated into a digital platform that virtually replicated the factory plant in a Digital Twin system. OEE was automatically calculated based on three main indicators: Availability, Performance, and Quality. Simulations in the virtual environment identified production bottlenecks and allowed predictive actions to prevent failures and optimize machine performance. The results, obtained over 80 days of monitoring, showed an evolution in productive efficiency indicators, with a reduction in unplanned downtime, dynamic adjustment of production parameters, and improvement in product quality, positively impacting industrial sustainability and energy efficiency.