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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13 resultados
Resultados da Pesquisa
Item Industrial Engineering and Operations Management(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) JUNIOR, Milton Vieira; LEITE, Jandecy CabralThe book published by Springer presents an in-depth approach to industrial engineering and operations management. It brings together several research studies and case studies that explore innovative methodologies, emerging trends and efficient practices in modern industrial environments.Item Aplicação do DEMATEL para avaliação das barreiras à robotização no abastecimento de materiais em indústria de componentes eletrônicos no Polo Industrial de Manaus(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) COSTA, Julianny Oliveira da; RODRIGUEZ, Carlos Manoel TaboadaThe growing need for industrial modernization has highlighted the importance of robotization in production processes, especially in the Manaus Industrial Pole (PIM), one of Brazil's main industrial complexes. Despite the potential benefits for competitiveness and operational efficiency, the implementation of robotic technologies faces obstacles in the region's electronics component industries. This technological gap, in an increasingly automated global scenario, raises questions about the factors hindering the modernization of these industrial processes. This study focuses on the barriers to robotization in material supply in production lines in the electronics component sector of the Manaus Industrial Pole, a critical process for operational efficiency. To this end, a systematic literature review was conducted, aiming to outline the current state of academic research on the subject and identify a set of barriers to the implementation of robotization. These barriers were categorized, selected, and legitimized by industry and academic experts through structured questionnaires applied via Google Forms. The responses obtained from the legitimation of the barriers by experts and the application of the Decision Making Trial and Evaluation Laboratory (DEMATEL) methodology allowed the most relevant barriers to be prioritized for further evaluation. This process was fundamental to direct the research efforts and ensure that the results were relevant to the context of the Manaus Industrial Pole. The results highlighted three main barriers as the most impactful: high initial costs, cultural resistance within organizations, and lack of adequate technological infrastructure. The DEMATEL method also revealed how these factors interrelate, influencing the adoption of robotic technologies. It is expected that the findings of this research will provide valuable subsidies to overcome these challenges, facilitating the integration of robotic technologies into the production processes of the PIM and strengthening the competitiveness of the sector in the region.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, 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 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.Item DESENVOLVIMENTO DE SISTEMA DE CONTROLE DE DRONES PARA ENTREGA DE PRODUTOS COM MICROCONTROLADORES(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) ALENCAR, David Barbosa de; LEITE, Jandecy CabralThis chapter discusses the development of a control system for drones aimed at product delivery, using microcontrollers as the technological base. The goal is to improve logistics processes, reducing delivery time and optimizing operations in hard-to-reach areas. The proposed solution is based on programming microcontrollers for flight control and automated navigation. The results demonstrated the system's feasibility, highlighting the precision and efficiency of drones in small-scale distribution tasks.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 Indústria 4.0: uma proposta para implementação em uma empresa metal mecânica no Polo Industrial de Manaus(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) PEREIRA, Danilo Serrão; GUIMARÃES, Gil EduardoThis work presents a proposal for the implementation of Industry 4.0 technologies in a mechanical metal company located in the Industrial Pole of Manaus (PIM). The research addresses the company's maturity level regarding Industry 4.0 using the Impuls questionnaire as the main tool. Through detailed analysis, the key gaps and opportunities for the company's digital transformation are identified, focusing on areas such as automation, data analytics, and system integration. The study proposes a roadmap for the implementation of Industry 4.0 technologies, with specific steps for automating production processes and workforce training. Additionally, challenges such as resistance to change and the shortage of qualified labor are discussed, along with strategies to overcome them. The research concludes that transitioning to Industry 4.0 is essential to enhance the company's competitiveness, promote sustainability, and improve operational efficiency.Item Sistema de rastreabilidade no processo produtivo por meio da Indústria 4.0: monitoramento computacional da trajetória da matéria-prima ao produto final(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) BARBOZA, Sérgio Lyra; LEITE, Jandecy CabralThe research presents the proposal for an intelligent system with an interactive interface for tracking raw materials in the manufacturing environment. Using technologies made available by Industry 4.0, a system was developed capable of tracking raw materials from arrival at the factory to the final product, helping interested sectors monitor the status of inputs. The specific objectives involve technical software design with requirements specification, prototyping using interface creation tools, UX, UML, and Wireframes, development of software architecture, business classes, communication with databases and data capture devices, configurations on the local server, development of Programmed Application Interfaces, development of the interface manager and their connectivity, data analysis, and presentation of interfaces used. The methodology used was Incremental, where the system is built and implemented gradually in small functional increments. The proposed implementation uses a sensing system for monitoring products with RFID. The physical-technological infrastructure includes RFID tags, thermal label printers, and portals for real-time recognition of raw material, intermediate product, and finished product. The data is collected and processed promptly to be made available to the user through an interactive interface. This study represents a significant contribution to the advancement of manufacturing processes and intelligent management in stock and inventory systems.Item Kanban Eletrônico com Inteligência Artificial: Desenvolvimento e Implementação de uma Solução para Transformação Digital e Otimização Produtiva em uma Indústria de Fitas do PIM(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) ARAÚJO, Lívia Fernanda Lobão de; GUIMARÃES, Gil Eduardo; MARINELLI FILHO, Nelson; SCHMIDT, Fabricio Carlos; CORREA, Geraldo Nunes; GUIMARÃES, Gil EduardoThis study details the development and application of an electronic Kanban system integrated with Artificial Intelligence (AI) in a company from the Industrial Pole of Manaus (PIM). The research follows the principles of Industry 4.0, focusing on optimizing production sequencing, improving operational efficiency, and reducing costs. The methodology combined exploratory and applied approaches, employing qualitative and quantitative methods to map bottlenecks and create customized technological solutions. The results demonstrate significant advances, including a 67% reduction in order registration time, a 22% increase in overall equipment efficiency (OEE), and an 18% reduction in non-conformities identified in the final inspection. The study highlights the transformative impact of digitization and automation on modernizing PIM companies and presents a practical and replicable model to address similar challenges in the Brazilian industrial context.Item Embedded Systems for Energy Efficiency of Climate Environments(Instituto de Tecnologia e Educação Galileo da Amazônia, 2022) CASTRO, Hilton Barros de; LEITE, Jandecy Cabral; GARCIA, Bianca Figueiredo; LEITE, Jandecy CabralElectricity consumption increases as technology advances, making energy efficiency crucial. This study proposes a system based on hardware and software to control climate environments automatically, reducing electricity consumption, increasing the lifespan of climate control devices, and improving thermal comfort. The developed technology uses sensors to measure ambient temperature, detect human presence, and automatically adjust climate control devicesItem Sistema de irrigação automatizado orientado pela compensação da evapotranspiração da cultura(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) SILVA, Edivaldo Amarante da; NASCIMENTO, Manoel Henrique ReisThe imbalance between population growth and agricultural production increases the demand for food, making irrigation efficiency essential for food security. This study develops an automated irrigation system based on the Penman-Monteith method to calculate evapotranspiration and irrigation pulse. An experiment compared methods based on evapotranspiration and accumulated radiation, showing the former was 7% more water-efficient. The system uses an ESP32 microcontroller, radiation, humidity, and temperature sensors, promoting water savings and better agricultural management.