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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5 resultados
Resultados da Pesquisa
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.Item Sistema Automatizado para Monitoramento e Gerenciamento das Pulseiras Eletrostáticas por Meio de Dashboard(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) MAUÉS, Elvis Jardim; LEITE, Jandecy CabralThis document certifies the registration of the software entitled "Automated System for Monitoring and Managing Electrostatic Wristbands via Dashboard." Developed in C++, the system enables real-time control and monitoring of electrostatic wristbands used in industrial environments, with data visualization through an intuitive dashboard. The program aims to enhance safety and operational efficiency, providing an innovative solution for managing electrostatic devices.