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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19 resultados
Resultados da Pesquisa
Item Desenvolvimento de um sistema inteligente para secagem e cura autônoma na fabricação de produtos autoadesivos(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SOUZA, Raimundo Alberto Farias de; SANTOS, Eliton Smith dosThe production of reflective strips requires high precision and efficiency, especially for traffic signage and automotive applications. However, traditional drying and curing methods for chemical layers, such as paints and varnishes, rely on long outdoor periods, compromising product quality and reducing productivity. This study proposes the development of an integrated hardware and software model that allows automatic detection of the curing level, using controlled light radiation sources to accelerate the drying process and ensure greater uniformity. The research includes the creation of a controlled environment prototype and a Human-Machine Interface (HMI) monitoring system to optimize industrial production. The theoretical foundation is based on the application of ultraviolet (UV) photopolymerization technology, aiming to improve product quality, production efficiency, and process sustainability.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 Optimization of Economic and Environmental Dispatch Using Bio-inspired Computer Metaheuristics(Instituto de Tecnologia e Educação Galileo da Amazônia, 2023) NASCIMENTO, Manoel Henrique Reis; CAMPOS, Paola SoutoThis chapter addresses the optimization of economic and environmental dispatch in electric power systems using bio-inspired computational metaheuristics. Techniques such as Genetic Algorithms, Particle Swarm Optimization, and Ant Colony-Based Algorithms are analyzed. The study demonstrates how these approaches can reduce operational costs and minimize environmental impacts, ensuring energy efficiency and sustainability.Item Desenvolvimento de um Sistema de Automação Residencial com I.A. para Detectar Quedas de Idosos e Envio de Alertas(Instituto de Tecnologia e Educação Galileo da Amazônia, 2023) Alencar, David Barbosa de; LEITE, Jandecy CabralThe article presents a proposal for the development of a home automation system using Artificial Intelligence (AI) to detect falls in the elderly. This system aims to ensure the safety and well-being of the elderly, who face a high risk of falls and their consequences for health and quality of life. With the aging of the population worldwide, the implementation of technological solutions that can assist in the care of the elderly is increasingly necessary. AI is a promising technology for identifying behavior patterns and accurately detecting falls, and can send alerts to caregivers or family members in real time. In addition, the integration of the system with other home automation devices can further improve the safety and comfort of the elderly. Recent studies also show the effectiveness of technology in detecting falls in the elderly and improving their quality of life.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, 2024) MACIEL, Lincoln Fábio Luiz; NASCIMENTO, Manoel Henrique ReisThe transition to Industry 4.0 has brought significant advances in production processes, where the application of Artificial Intelligence (AI) technologies has transformed entire sectors, including the manufacturing of lithium-ion batteries. This work addresses the development of an intelligent system focused on improving the cutting of battery terminals, using AI algorithms to optimize precision and reduce defect rates. The central problem is the imprecision in cutting the terminals of lithium-ion batteries, leading to a high rate of defective or unusable products. This issue not only increases production costs due to material waste but also negatively impacts the overall efficiency of the manufacturing process. To achieve this goal, a methodology was used for the application of machine learning and real-time data analysis, which enabled automatic adjustments in the cutting process, promoting a flexible and adaptable manufacturing environment. The results obtained from the application of the system indicate a significant reduction in the rate of defective batteries, as well as an increase in the quality and uniformity of the produced terminals. This efficiency gain demonstrates the potential of AI to meet the requirements of quality and precision while simultaneously reducing production costs. The integration of AI technologies in the process of cutting lithium-ion battery terminals not only promotes improvements in quality and sustainability but can also generate a significant competitive advantage for the renewable energy and storage sector in flexible manufacturing processes.Item Utilização de Inteligência Artificial e IoT para Inspeção e Detecção de Defeitos em Placas de Circuito Impresso(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) SOARES, Karen Kettelen Souza; GUIMARÃES, Gil EduardoThe increasing complexity in the manufacturing of printed circuit boards (PCBs) has posed significant challenges for industries, particularly in the inspection and detection of defects. This study proposes the use of Artificial Intelligence (AI) and the Internet of Things (IoT) as tools to optimize fault detection in PCBs, focusing on reducing human errors and improving operational efficiency. The research is based on the implementation of an automated inspection system, utilizing neural networks for defect classification and IoT sensors for real-time monitoring of manufacturing conditions. The main goal of the dissertation is to develop an efficient analysis model to identify early faults, enhance product quality, and reduce operational costs. The study involved building a functional prototype that integrates AI and IoT, validated in a real production environment. The results showed that the proposed approach could detect defects with higher accuracy, leading to significant improvements in the efficiency of the PCB production line.Item Arquitetura computacional para controle de monitoramento de qualidade de energia utilizando ferramentas de inteligência artificial focado na Indústria 4.0 com integração de energias renováveis(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) KAMIO, Edson; GUIMARÃES, Gil EduardoElectric power quality (QEE) is crucial for the efficiency of industrial systems in Industry 4.0. This dissertation proposes an innovative computational architecture to control and monitor QEE, integrating renewable energy sources and artificial intelligence (AI). Key metrics like power factor (PF) and total harmonic distortion (THD) directly influence operational costs and equipment lifespan. AI-based predictive strategies dynamically manage capacitor banks and harmonic filters, mitigating issues such as inadequate PF and high THD. Reactive power compensation (CPR) is central to improving PF, reducing system losses, and enhancing energy efficiency. The system also integrates solar energy management, optimizing energy savings and sustainability. Data is collected using IMS Smart Cap 485 devices via the Modbus-RTU protocol, measuring voltage, current, active/reactive power, and THD. Stored in a MySQL database, the data is analyzed in real time with deep learning (LSTM) and optimization (AG) algorithms. Python-based dashboards visualize data, predict network issues, and support strategic actions, such as activating capacitors and THD filters. This approach highlights AI's role in energy efficiency and reducing reliance on conventional sources. Gaps in literature include the lack of interoperability standards, the need for explainable AI algorithms, and limited longitudinal studies on real-world applications. This research addresses these challenges, contributing to Industry 4.0's sustainability and efficiency goals.Item Development of Intelligent Devices for Communication and Data Pre-Processing in the Process of Electronic Meter Testing(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 CabralThis study investigates the development of intelligent devices for communication and data pre-processing in electronic meter testing. The research addresses the lack of efficient communication between electronic devices and the need for information synchronization to support decision-making in Industry 4.0. The article presents the development of a Lean Manufacturing Intelligent System, integrating API and machine learning algorithms for demand forecasting and process optimization. The results include embedded firmware for data collection, forecasting algorithms, and an interactive dashboard for production monitoring. The proposed solution aims to reduce costs and improve product quality.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 CabralLean Manufacturing is a strategic methodology aimed at reducing production waste, ensuring product quality, and optimizing delivery times. However, many electronic meter manufacturing companies lack the necessary technologies to effectively implement this methodology. This study proposes the development of an Intelligent Lean Manufacturing System based on the requirements of a Manufacturing Execution System (MES), utilizing technologies such as Artificial Intelligence, the Internet of Things, and Embedded Systems. The system enables real-time decision-making for production control and management, reducing costs and improving product quality.Item Sistema Fuzzy para Avaliação Inclusiva e Sustentável (SFAIS)(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) BRITO JUNIOR, Jorge de Almeida; LEITE, Jandecy CabralThis document certifies the registration of the software Fuzzy System for Inclusive and Sustainable Evaluation (SFAIS), developed in the Python programming language. The system applies fuzzy logic to evaluate inclusion and sustainability parameters in different contexts, enabling more precise and adaptable analysis. The software was registered with the National Institute of Industrial Property (INPI) under number BR512025000363-3, valid for 50 years from January 1st following the date of 12/18/2024.