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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Agora exibindo 1 - 10 de 67

Desenvolvimento de um dispositivo para eliminar contato manual, reduzir esforço repetitivo e riscos ergonômicos, melhorando a qualidade e reduzindo custos – otimização de processos industriais no Polo Industrial de Manaus (PIM)
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) CRUZ, Cristovão Santiago da; GUIMARÃES, Gil Eduardo
The present work aims to optimize the execution of a manufacturing process by making a practical device to assemble the steel balls and lubricate the motorcycle column tube with grease, thus eliminating the manual contact of the employee with the balls and grease, reducing repetitive effort and also ergonomic risks, following NR17, meeting the safety standards present in NR12 and increasing the efficiency of the production process, improving quality, reducing costs and avoiding injuries to the employee. The company where the project was implemented is located in a strategic area, in the heart of the Americas and the Amazon in the Manaus Industrial Complex, which is one of the most modern industrial and technological centers in all of Latin America. The project was implemented in a factory in the Manaus industrial complex in the two-wheel sector, in the production sector of the Assembly Line. The results showed that the automated device reduced physical effort, eliminated contact with grease, increased assembly precision, and significantly reduced operating costs.
Sistema inteligente de supervisão e controle de capacidade em processos industriais: interação de SCADA, IA e aprendizado de máquina
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) ARAUJO, Nelson Michel Matos de; MARINELLI FILHO, Nelson
This study proposes a machine learning-based system for capacity supervision and control in industrial automation. The solution integrates high-precision sensors, programmable logic controllers (PLCs) and a SCADA (Supervisory Control and Data Acquisition) system, allowing real-time monitoring and adjustment of manufacturing processes. The methodology included the development of a software in C# in the Visual Studio 2015 environment, with an interface in a Mi PLC Mitsubishi CPU Q03UDV, and the implementation of the system on a production line for practical evaluation. The results demonstrated the system's ability to maintain the process capability indexes (CpK) above the critical limits (1.33) through the automatic correction of deviations. Key highlights include efficient integration with industrial networks and dynamic adaptation to production variabilities. On the other hand, limitations were identified, such as the dependence on a robust infrastructure and challenges in environments with high electromagnetic interference. The discussion highlights the potential for scalability, application in other industrial contexts, and the inclusion of advanced algorithms, such as neural networks, to enhance predictive capacity to improve predictive ability. Future work suggests exploring more affordable implementations for small and medium-sized businesses, integration with IoT for predictive maintenance, and sustainability assessments. This research contributes to the advancement of intelligent automation, promoting consistent quality and operational efficiency in manufacturing.
Metodologia para avaliar nível de maturidade da indústria 4.0 e sua correlação com atributos do metaverso industrial
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) SOUZA, Patrícia Nunes de; GUIMARÃES, Gil Eduardo
Since Facebook changed its name to Meta, the term "Industrial Metaverse" has been widely disseminated in industrial sectors. This study aims to establish a simple and accessible methodology for companies of different sizes to assess the maturity level of Industry 4.0 tools to prepare the foundations for future implementations in the industrial metaverse. A bibliographic review was conducted to identify the main enabling tools of Industry 4.0 and the attributes of the metaverse according to Weinberg and Gross (2023). Based on this information, a correlation table was developed to guide companies in preparing for the development of metaverse applications. The methodology was applied to a company in Manaus, allowing the assessment of the maturity level of Industry 4.0 tools and identifying critical points for supporting future metaverse initiatives. The results indicated that the company has the potential to implement immersive technologies but needs to improve the interoperability and scalability of internal systems.
Otimização da produção de baterias de lítio: implementação de tecnologias da indústria 4.0 no polo industrial de Manaus
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) DAMASCENO, Alexandre Holanda; LEITE, Jandecy Cabral
This work addresses the integration of cyber-physical systems for the automation of industrial processes at the Manaus Industrial Pole (PIM), with a focus on lithium battery production. The justification for the study is anchored in the growing demand for electronic devices, which requires greater efficiency and quality in battery production while seeking to reduce operational costs and improve worker ergonomics. The theme of the study involves the application of Industry 4.0 technologies, with the aim of modernizing the production process of the Manaus Industrial Pole, aligning it with global market demands and the need for automation. The objectives of the work included the creation of an automation prototype consisting of 12 stations, in order to increase precision, reduce variability, and improve the performance of the production line. Furthermore, real-time monitoring systems and advanced robotics were integrated to optimize the critical phases of battery production. The methodology used involved mapping the previous manual production process, followed by the implementation of an automated system. Comparative data on efficiency, rejection rate, and cycle time were collected before and after automation to assess the impact of improvements. The main results indicate a significant increase in productivity, with a reduction in cycle time from 5 to 3 minutes and a drop in the rejection rate from 12% to 3%. Automation also contributed to a reduction in operational costs and an increase in overall equipment efficiency. The conclusions indicate that modernization, aligned with Industry 4.0 technologies, brought substantial gains in terms of competitiveness, quality, and sustainability.
Sistema ciberfísico na indústria 4.0 - aplicado em testes de deficiência dielétrica em unidades evaporadoras de aparelhos de ar condicionado
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) ALENCAR, Wanderson Gray Rodrigues de; ALENCAR, David Barbosa de
Cyber-physical systems (CPS) have played 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 the dielectric strength test of air conditioning evaporators, an essential component for the safety and efficiency of equipment. The main objective was to model an automated control system that integrates CPS to monitor and optimize dielectric tests, overcoming the limitations of traditional methods. The research included mapping the electronic testing process, identifying operational bottlenecks, gathering requirements for system modeling and comparative evaluation between traditional and automated methods. The proposed system integrates SCARA robots, industrial vision cameras and HIPOT devices, controlled by a PLC (Programmable Logic Controller). The results indicate significant improvements in accuracy, safety, efficiency and traceability, reinforcing the potential of adopting CPS for critical industrial processes.
Hardware didático para mapeamento indoor com LiDAR: uma abordagem para a Indústria 4.0
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) GUABIRABA, Rafael Braga; MARTINELLI FILHO, Nelson
The Manaus Industrial Hub is an innovation center driven by industry, government, and education, requiring accelerated workforce qualification for Industry 4.0. The rapid technological transition demands effective training strategies, reducing dependence on external models. Therefore, the development of accessible educational systems is essential to prepare professionals for this new reality. This dissertation proposes a compact architecture capable of supporting ROS, focusing on indoor environment mapping. This platform is designed for educational purposes, providing an introductory experience in robotics. The selected materials prioritize portability, utilizing a Raspberry Pi 4 Model B and an RPLidar 360° laser sensor. The results demonstrate the system's feasibility for both educational and industrial applications, contributing to the training of skilled professionals for Industry 4.0.
Elaboração de uma matriz de tomada de decisão, com lógica fuzzy, sobre a adoção de tecnologias 4.0 em uma linha de montagem, por meio de gêmeos digitais, com ênfase na mão de obra humana e sistemas robóticos
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) MONTEIRO, Manoel de Assis; GUIMARÃES, Gil Eduardo
This study presents the design and analysis of a new production line within the Industry 4.0 framework, emphasizing the interaction between human labor and advanced robotic systems. The research employs digital twin simulation to model and compare two production scenarios: a traditional one, operated exclusively by humans, and an automated system integrating collaborative robots (COBOTs). The methodology uses Plant Simulation software to assess key performance indicators such as productivity, operational costs, worker fatigue, safety, and ergonomic impact. The results highlight significant improvements in production efficiency, cost reduction, better working conditions, and enhanced industrial sustainability. Furthermore, the study discusses the social and economic implications of automation, emphasizing the need for workforce reskilling and adaptation to new technological demands. It is concluded that the strategic integration of robotic systems and digital technologies not only enhances industrial competitiveness but also fosters a safer and more ergonomic working environment, aligned with the trends of smart manufacturing.
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
This 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 electronic board assembly line at the Manaus Industrial Complex (PIM). The objective was to develop a solution capable of identifying, in real time, the times and reasons for production stops, aiming to optimize industrial processes and reduce operational costs. The data was collected through IoT sensors installed in the production lines, integrated into a digital platform that virtually replicated the manufacturing plant in a Digital Twin system. The OEE was automatically calculated based on the three main indicators: Availability, Performance, and Quality. Simulations in the virtual environment identified production bottlenecks and allowed predictive actions to avoid failures and optimize machine performance. The results, obtained over 80 days of monitoring, showed progress in production efficiency indicators, with a reduction in unscheduled downtime, dynamic adjustment of production parameters, and improvement in product quality, positively impacting sustainability.
Sinergia entre Modelagem 3D e Redes Neurais Artificiais na Otimização da Manufatura Aditiva no Contexto da Indústria 4.0
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) DIAS, Jonathan Oliveira; ALENCAR, David Barbosa de
Additive manufacturing (AM), widely known as 3D printing, emerges as one of the key technologies of Industry 4.0, enabling the production of parts with high geometric complexity and customization. This study investigates how the integration between 3D modeling and Artificial Neural Networks (ANNs) enhances the efficiency and quality of AM processes. 3D modeling supports detailed simulations of material behavior and manufacturing processes, while ANNs provide predictive analysis and learning from large data volumes, allowing automatic and dynamic adjustments to parameters such as speed, temperature, and fill patterns. The results show significant improvements in reliability, waste reduction, and energy consumption, aligning production with sustainability demands.
Business Intelligence as an Integration Tool for Fault Detection of the Board Assembly Process
(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) PAIXÃO, Elisete da Silva; LEITE, Jandecy Cabral
The plate assembly process in the company in question has a stipulated goal of 2000 plates per day, and 10% of this production has failures, compromising management-defined objectives. This study proposes the implementation of an intelligent system for identifying and correcting failures in the board assembly process using Business Intelligence (BI) tools to advance Industry 4.0 practices. The methodology included Process Mapping and Requirement Analysis for the Integrated System Implementation. The integrated system enabled faster and more effective communication with other production systems, providing assertive information for data security and usability. The application of BI represented a significant step towards automation and continuous improvement in the industrial environment.

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