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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Resultados da Pesquisa
Item Uso da Metodologia e Ferramentas Lean na Gestão da Produção para Melhoria da Eficiência do Processo Produtivo - Estudo de Caso em uma Empresa do PIM(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) ALMEIDA, Melry Silva de; VIEIRA JUNIOR, Milton; SILVA, Carlos Américo de Souza; FERREIRA, Anderson da Silva; LEITE, Jandecy CabralA competitividade global e a complexidade produtiva nas indústrias modernas destacam a necessidade de métodos para melhorar eficiência e produtividade. A modernização industrial enfrenta desafios como processos complexos, variabilidade da demanda e limitações de recursos, exigindo soluções rápidas e assertivas para evitar ineficiências e perda de competitividade. No Brasil, o Polo Industrial de Manaus (PIM) exemplifica como metodologias e ferramentas como Lean Manufacturing, gráfico de Yamazumi, Ishikawa, Balanceamento de Linha, 5 Porquês, 5W2H, Matriz Básica ajudam a superar custos logísticos e pressões regulatórias, otimizando recursos e demandas. Juntamente com o Planejamento da Produção, essas metodologias e ferramentas minimizam custos, maximizam produtividade, eliminam desperdícios e gargalos, aumentando a competitividade. Focando na fabricação de caixas acústicas, esta pesquisa qualitativa, exploratória, através de um estudo de caso com realização de pesquisa bibliográfica e documental, identificou práticas para otimizar processos e resolver problemas, gerando melhorias na taxa de produção com aumento de 21,9% na capacidade produtiva e da eficiência da mão de obra com uma redução de 10,7% no número de operadores na linha, gerando um impacto positivo nos resultados empresariais.Item 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 EduardoThe 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.Item 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, NelsonThis 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.Item 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 EduardoSince 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.Item 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 CabralThis 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.Item 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 deCyber-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.Item Melhoria de desempenho em equipamentos de manufatura: um estudo de caso sobre a redução de queimas de placas eletrônicas em máquinas Okuma(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) SANTOS, James Silva dos; BRITO JUNIOR, Jorge de AlmeidaThis study addresses the performance improvement of Computer Numerical Control Okuma machines at Musashi da Amazônia Ltda., focusing on reducing failures in electronic boards caused by electromagnetic interference in the manufacturing environment. The primary objective was to decrease the incidence of these failures, enhance operational efficiency, and reduce maintenance costs. The methodology involved analyzing historical data, identifying interference sources, and installing electromagnetic interference filters. As a result, the filters significantly reduced failures, ensuring greater operational stability and lower costs. This work highlights the importance of power quality management for industrial efficiency.Item Proposta de um algoritmo de detecção de falhas com lógica fuzzy para otimização de motores elétricos em processos de fundição de alumínio(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) SILVA, Lenildo Marcos da Mota; BRITO JUNIOR, Jorge de AlmeidaThis study proposes the development of a fault detection system based on fuzzy logic to optimize electric motors in aluminum casting processes. The theme is grounded in the need to enhance efficiency and operational continuity in the casting industry, minimizing unplanned downtime and maintenance costs. The primary objective is to create a fuzzy control model that enables real-time monitoring of critical variables, such as temperature, pressure, and electric current, to facilitate predictive fault detection. Methodologically, operational scenario simulations were conducted to evaluate the model’s performance under adverse conditions, including overload and overheating, with validation through experimental testing. Results indicate that the proposed fuzzy system accurately identifies anomalies and issues preventive alerts, extending motor lifespan and reducing downtime. It is concluded that the model can be integrated with supervisory systems like SCADA, enhancing predictive maintenance and operational efficiency. This technological solution shows promise for the aluminum casting industry and potential applications in other industrial sectors.Item Implementação de um sistema de visão com deep learning para otimizar o processo de inspeção de emendas das bobinas na fabricação do cinturão de segurança(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) SOUZA, Kerlisson Silva de; SANTOS, Eliton Smith dosProduct quality is one of the primary criteria considered by customers when choosing an item. Additionally, it is an essential factor for companies to stand out in a highly competitive market. In the Manaus Industrial Hub (PIM), in a machine used for producing safety belts, defect detection is a crucial stage in the production process. To enhance this task, Artificial Intelligence (AI) was implemented, standing out for its high efficiency in analyzing and processing data in industrial environments. The data was captured in image format by a camera, and using Deep Learning (DL) techniques, an intelligent algorithm capable of detecting faults was developed. Due to its autonomous learning capability and ability to identify and characterize defects, this algorithm represents the future of automated inspection. It has already achieved significant success in applications such as object identification and classification, facial recognition, and fault diagnostics. Given this context, the aim of this study is to propose an ideal solution to minimize failures in the production process of safety belts. The proposal seeks to automate the currently manual step using the concept of computer vision with AI, ensuring greater efficiency and reliability in the production process. The research, development, and application of AI with the algorithm in the case study were conducted in the R&D laboratory of the company located in the Manaus Industrial Hub (PIM). The project utilized product inputs, a camera equipped with a lens for capturing images, and a computer for data storage and algorithm development. The application of AI in this environment uses computer vision systems to process image data. For this, a program was developed in Python with the PySimpleGUI library. The trained model was evaluated based on loss and accuracy metrics on the test set, achieving values of 0 and 100%, respectively. During testing, new belts were used, reaching 100% accuracy in the results. The proposed model showed excellent results. With data processed by AI using Deep Learning (DL) techniques, real-time inspection of the belts was achieved. Additionally, the network achieved perfect accuracy in all tests conducted on the belts, demonstrating the effectiveness of the solution.Item Uso da metodologia e ferramentas Lean na gestão da produção para melhoria da eficiência do processo produtivo – estudo de caso em uma empresa do PIM(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) ALMEIDA, Melry Silva de; VIEIRA JÚNIOR, MiltonDue to global competitiveness and production complexity in modern industries, the need for methods to improve efficiency and productivity is highlighted. Given the growing need for industrial modernization, challenges such as process complexity, demand variability and resource limitations, there is a need for fast and assertive solutions, at the risk of inefficiencies and loss of competitiveness. In Brazil, the Manaus Industrial Park (PIM) is an example of how methodologies and tools, such as Lean Manufacturing and VSM, help to overcome challenges such as logistics costs and regulatory pressures, optimizing resources and meeting demand efficiently, together with Production Planning, defining strategies and coordinating operations to minimize costs and maximize productivity. The use of Quality and Production Management methodologies and tools are essential to improve production processes and ensure greater control, as well as focusing on eliminating waste and variations, identifying bottlenecks and optimizing flow. These methodologies and tools combined increase efficiency, improve quality and reduce costs, directly contributing to the competitiveness of companies in the global market. Focusing on the speaker manufacturing industry, the research, conducted in the form of a case study with a qualitative approach, explores the identification of practices to optimize production processes together with production planning, so that they can also be used in problem-solving, to maximize results and the impacts generated for the company. Through the application of these practices, improvements were achieved in the production rate and labor indicators used.