Artigos
URI permanente para esta coleçãohttps://rigalileo.itegam.org.br/handle/123456789/5
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Item Desenvolvimento de um Dispositivo Inteligente de Monitoramento de Energia Elétrica Integrado à Plataforma SGE com Aplicação da Lógica Fuzzy para Tomada de Decisão na Gestão Energética da Indústria 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SANTOS JUNIOR, Hélio Andrade dos; ALENCAR, David Barbosa de; SANTOS, Eliton Smith dos; CAMPOS, Paola Souto; MORAES, Nadime Mustafa; SANCHES, Antônio Estanislau; LEITE, Jandecy CabralEfficient management of electrical energy in industrial environments is a crucial challenge, exacerbated by the continuous increase in consumption and frequent inefficiencies in resource utilization. In this context, Industry 4.0 and Smart Grids emerge as promising approaches, integrating advanced digital technologies to optimize energy production, distribution, and consumption. This study developed and validated a portable electrical energy monitoring device integrated into the SGE platform, applying fuzzy logic to support real-time decision-making. The device demonstrated the ability to conduct detailed analyses of energy consumption and efficiency, enhancing the accuracy in detecting losses and critical inefficiency points.Item Sistema Ciber-Físico na Indústria 4.0 - Aplicado em Testes de Rigidez Dielétrica em Unidades Evaporadoras de Aparelhos de Ar-Condicionado(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) ALENCAR, Wanderson Grey Rodrigues de; ALENCAR, David Barbosa de; SANTOS, Eliton Smith dos; CAMPOS, Paola Souto; MORAES, Nadime Mustafa; SANCHES, Antônio Estanislau; LEITE, Jandecy CabralCyber-physical systems (CPS) play 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 dielectric strength testing of air conditioning evaporator units, essential for ensuring equipment safety and efficiency. The main objective was to develop an automated control system integrating CPS to monitor and optimize these tests, overcoming the limitations of traditional methods. The proposed system demonstrated significant improvements in accuracy, safety, efficiency, and traceability.Item Aplicação de Controle Fuzzy em Microgrids Solares como Auxílio na Mitigação de Interrupções em Comunidades Isoladas no Amazonas à Portaria Nº 140/2022(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SILVA NETO, Oswaldo Wanderley da; ALENCAR, David Barbosa de; SANTOS, Eliton Smith dos; BRITO JÚNIOR, Jorge de Almeida; SANCHES, Antonio Estanislau; LEITE, Jandecy CabralIsolated communities in the Amazon face significant challenges in accessing reliable energy due to logistical difficulties and lack of infrastructure. Photovoltaic microgrids emerge as a viable alternative but suffer from instability and frequent interruptions caused by environmental variability. This study investigates the implementation of fuzzy control in these systems to mitigate supply failures and improve operational efficiency, in compliance with INMETRO's Portaria No. 140/2022. The results show that fuzzy control is a promising solution to enhance the reliability and sustainability of energy in isolated communities.Item Aplicação da lógica Fuzzy na emissão de notas fiscais em processos administrativos na Indústria Lean Office 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SOARES, Vera Alana Nobre; ALENCAR, David Barbosa de; SANTOS, Eliton Smith dos; CAMPOS, Paola Souto; MORAES, Nadime Mustafa; LEITE, Jandecy CabralIndustry 4.0 has brought the need to integrate advanced technologies to improve the efficiency and agility of administrative processes. This study proposes the application of fuzzy logic to optimize the issuance of invoices, a critical process that faces challenges such as manual errors, delays, and high costs. A fuzzy model was developed that identifies key variables, applies inference rules, and tests the solution in a real environment with operational data. The results indicate a significant reduction in errors and processing times, in addition to gains in tax compliance and customer satisfaction.Item Digital Technologies Review for Manufacturing Processes(Instituto de Tecnologia e Educação Galileo da Amazônia, 2022) PARENTE, Ricardo Silva SILVA, Italo Rodrigo Soares SIQUEIRA JUNIOR, Paulo Oliveira UHLMANN, Iracyanne Retto; LEITE, Jandecy CabralThe industrial processes transformation caused by Industry 4.0 is advancing in countries like China, Japan, Germany, and the United States. However, developing countries such as Brazil still face challenges in adapting to the digital era. This study presents a review of the main technologies used in smart manufacturing and the challenges of its implementation in Brazil. The research was based on 114 articles and two books collected from the Web of Science database. The results indicate that the primary challenges for Industry 4.0 adoption in Brazil include poor technological infrastructure, lack of investment in technology, and insufficient training of qualified professionals. Although the study focuses on the Brazilian scenario, its conclusions are applicable to other emerging countries, providing a general overview of concepts and practical applications developed by the international academic community.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 CabralThe Lean Manufacturing process is a strategic methodology aimed at reducing production waste, ensuring product quality, minimizing delivery time, and reducing defects. However, the company analyzed lacks technologies that enable the effective implementation of this methodology. This study proposes the development of an Intelligent Lean Manufacturing System based on the requirements of a Manufacturing Execution System (MES), assisting decision-making in production control and management through technologies such as Artificial Intelligence, Internet of Things (IoT), and Embedded Systems. The system includes Deep Neural Network (DNN) algorithms to forecast demand, optimize processes, and monitor real-time indicators. The research demonstrates that the application of these technologies can reduce costs and improve production quality, raising manufacturing maturity levels to Industry 4.0 standards.Item Development of an Intelligent System for Tracking RFID Tags Applied to Industry 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) SERRÃO, Alacy da Conceição da Silva LEITE, Jandecy Cabral SILVA, Ítalo Rodrigo Soares RIBEIRO, Paulo Francisco da Silva NASCIMENTO FILHO, Alarico Gonçalves do MENDONÇA, Pedro Henrique Barros; LEITE, Jandecy CabralThe market for traceability systems for software projects is rapidly expanding, driven by the growing demand for efficient monitoring and control solutions. This study aims to develop an RFID tag tracking system applied to Industry 4.0, addressing inventory and logistics process needs. The study covers software development with integration of Business Intelligence (BI), stock indicators, and business rules. Agile methodologies such as Extreme Programming (XP) and Kanban were applied, along with design patterns to ensure system robustness. Computational tests and simulations demonstrated that the developed system is efficient, ensuring transparency, security, and operational efficiency for the studied company in the Manaus Industrial Hub.Item Smart energy: application of the photovoltaic system using genetic algorithms for decision making in industry 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) OLIVEIRA, Adriana Waschington Carneiro de; SILVA, Simone da; ALMEIDA, Anderson Alexandre Silva de; MONTEIRO, Odilon Bentes; RIBEIRO, Paulo Francisco da Silva; NASCIMENTO FILHO, Alarico Gonçalves do; LEITE, Jandecy CabralThe growing demand for sustainable solutions and the digitalization of industrial processes have driven the adoption of photovoltaic systems and advanced decision-making technologies. In the context of Industry 4.0, where automation and artificial intelligence are fundamental, these systems stand out as a clean energy alternative, promoting savings and reducing pollutant emissions. This study aims to develop a photovoltaic energy control model that uses genetic algorithms to optimize energy efficiency in industrial environments, reducing costs and dependence on non-renewable sources. The methodology included the computational modeling of a photovoltaic system and the application of genetic algorithms to optimize parameters such as panel angle and operating hours, adapting the system in real time to variable consumption and generation conditions. The results showed that the use of genetic algorithms increased the system's efficiency by up to 20% compared to traditional methods, as well as minimizing consumption from the electricity grid at peak times. This study reinforces the importance of artificial intelligence in optimizing renewable resources, contributing to energy efficiency and sustainability in Industry 4.0.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 Eduardo; MARINELLI FILHO, Nelson; CORREA, Geraldo Nunes; TREVISOL, Janyel; LEITE, Jandecy CabralIndustry 4.0 introduces a comprehensive transformation in the production sector through the integration of advanced technologies, connecting the physical and digital environments. This study proposes a strategic plan for the implementation of Industry 4.0 in a metal-mechanical company in the Manaus Industrial Hub (PIM), using a structured roadmap. The research identified challenges and opportunities, highlighting barriers such as deficient infrastructure and lack of workforce training. The application of the Impuls questionnaire revealed that the company has an initial level of readiness for the technological transition. The proposed roadmap is divided into three phases: preparation and training, integration and automation, and continuous optimization with artificial intelligence. The study concludes that production modernization in the PIM can increase company competitiveness, reduce waste, and improve industrial sustainability.Item Desenvolvimento de um protótipo de gateway para coleta e transmissão de dados em sistemas de manuseio de materiais - Gate Move 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) AMARAL, Carlos Henrique; LEITE, Jandecy Cabral; RIBEIRO, Paulo Francisco da Silva; SILVA, Ítalo Rodrigo Soares; PARENTE, Ricardo Silva; DIRANE, Eduardo Nunes; MENDONÇA, Pedro Henrique Barros; LEITE, Jandecy CabralCurrently, material handling systems are fundamental in industries such as manufacturing, logistics, and distribution, performing critical functions in the movement, storage, control, and protection of materials throughout production and distribution processes. With the advancement of digital technologies and the emergence of Industry 4.0, there is a growing need for more intelligent and interconnected systems capable of collecting and transmitting real-time data, thus improving operational efficiency and decision-making. The primary objective of this study was to develop a gateway prototype called Gate Move 4.0, designed to efficiently and reliably collect and transmit data in material handling systems. The methodology adopted for the development of Gate Move 4.0 was organized into several stages, each meticulously planned to ensure that the final prototype met the established objectives. The study results showed that Gate Move 4.0 proved to be a functional prototype, meeting the proposed objectives and demonstrating satisfactory performance under various operating conditions.