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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41 resultados
Resultados da Pesquisa
Item Análise dos Desafios na Transição para Indústria 4.0: um Estudo Sobre a Integração de Sistemas de Custeio em Ambientes Automatizados(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SILVA, Maeli Oliveira da; MARINELLI FILHO, NelsonThis paper analyzes the challenges faced during the transition from traditional costing systems to absorption costing systems in the context of Industry 4.0. Through the analysis of heat maps applied to an industrial costing spreadsheet for electronic components, the study identifies and categorizes inconsistencies that reflect broader structural challenges of industrial digital transformation. The methodology was based on the application of data visualization techniques to identify null and zero values at different stages of the migration process. The results reveal seven critical categories of inconsistencies: interoperability issues, complexity in the allocation of indirect costs, implementation and maintenance costs, workforce training, real-time data management, compliance and security, and adaptation to the dynamics of Industry 4.0. It was concluded that such inconsistencies represent significant barriers to a successful transition, especially in industries with a high degree of automation. The study proposes a framework for assessing and mitigating these challenges, contributing to the literature on digital transformation in the Brazilian industrial context.Item Aplicação de Inferência Fuzzy Para Tomada de Decisão em Processos de SMT(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) LEITE, Herbety Lima; NASCIMENTO, Manoel Henrique Reis; ALENCAR, David Barbosa de; BRITO JUNIOR, Jorge de AlmeidaSoftware developed in Python applying fuzzy inference for decision-making processes in SMT (Surface-Mount Technology), targeting industrial process optimization. The registration is recognized under Brazilian intellectual property law and categorized within engineering and automation domains.Item Sistema inteligente para detecção de falhas utilizando algoritmo de Árvore de Decisão(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) PENEDO, Jorge Eduardo Santos; PALADINI, Edson Pacheco; SILVA, Carlos Américo de Souza; LEITE, Jandecy CabralPython-based software employing Decision Tree algorithms to detect faults in industrial or computational systems. Designed for Industry 4.0 environments, it aims to enhance operational reliability and enable automated diagnostics.Item Sistema inteligente para classificação de falhas na manufatura de placas utilizando algoritmo de Machine Learning KNN(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) PENEDO, Jorge Eduardo Santos; PALADINI, Edson Pacheco; SILVA, Carlos Américo de Souza; LEITE, Jandecy CabralPython-based software using the K-Nearest Neighbors (KNN) machine learning algorithm to classify failures in PCB manufacturing lines. Designed for Industry 4.0 environments, it aims to improve predictive failure detection accuracy in automated industrial contexts.Item Sistema inteligente para classificação de defeitos na manufatura de placas com Rede Neural Convolucional(Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) SILVA, Carlos Américo de Souza; LEITE, Jandecy Cabral; PENEDO, Jorge Eduardo Santos; PALADINI, Edson PachecoPython-based software designed to classify defects in PCB manufacturing using Convolutional Neural Networks (CNN). Applied in Industry 4.0 environments, the system improves fault detection efficiency and reliability in production lines through intelligent pattern recognition.Item Sistema integrado para detecção de falhas do processo de montagem de placas utilizando ferramenta de Business Intelligence para maturidade da Indústria 4.0.(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) PAIXÃO, Elisete da Silva; CAMPOS, Paola SoutoThe plate assembly process in a company has a target of producing 2000 plates per day; however, 10% of this production presents failures, compromising the management-defined goals. This study aims to implement an intelligent system for identifying and correcting failures in the board assembly process, based on Business Intelligence, aiming at the evolution of Industry 4.0 practices. The methodology included process mapping, analysis of requirements for implementing the integrated system, and evaluation of the system's effectiveness. The integrated system enabled communication between the various systems in the production process, providing more accurate information to improve usability performance and ensure data security. The implementation of this system represented a significant advancement for the evolution of Industry 4.0 practices, providing improvements in quality, efficiency, and cost reduction.Item Aplicação de Tecnologia da Indústria 4.0 na Melhoria dos Processos de Injeção Plástica em uma Empresa no Polo Industrial de Manaus(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) FERREIRA, Marcos Sidney Castro; CAMPOS, Paola Souto; LEITE, Jandecy CabralOptimizing lead times ensures that customer deadlines are met, thereby promoting customer satisfaction and loyalty. Additionally, reducing lead time leads to more efficient resource management, directly impacting the reduction of operating costs. This study aimed to implement Industry 4.0 technologies to improve plastic injection processes at a company in the Manaus Industrial Estate (PIM), reducing manufacturing costs, accelerating the lead time for device construction, and optimizing the time for developing new products. The methodology involved data collection on new production processes and the evaluation of the technology's impact on reducing manufacturing costs and improving lead time. This was done by mapping the current process flow, analyzing production loss reports, and examining production performance data. The results show a significant reduction in lead time, from 35 to 9 days. 3D printing also enabled the creation of more complex and precise devices, with less material waste, directly contributing to cost reduction and improved product quality.Item Smart energy: aplicação do sistema fotovoltaico utilizando algoritmos genéticos para tomada de decisão na Indústria 4.0(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) WASCHINGTON, Adriana Carneiro; SILVA, Simone daThe global energy transition and the need for energy efficiency in industrial environments are driven by the search for sustainability and the reduction of environmental impacts. This work addresses the application of genetic algorithms in the management of photovoltaic systems within the context of Industry 4.0, highlighting the concept of Smart Energy. The main objective is to investigate the benefits and impacts of this approach on energy efficiency, environmental sustainability, and the reduction of operating costs at the Manaus Industrial Estate (PIM). To achieve the objectives, methods based on computer simulation and analysis of real cases were used. The research included the modeling and development of genetic algorithms capable of optimizing variables such as energy generation, storage, and consumption in photovoltaic systems. Data was collected based on local climatic conditions, energy demand profiles, and industrial operating parameters. The results indicated that the genetic algorithms enabled significant gains in energy efficiency, with an average reduction of 20% in energy waste and 15% in operating costs. In addition, the model developed proved to be effective in adapting to climate variations and industrial demands, reducing dependence on non-renewable sources and greenhouse gas emissions. The conclusion is that integrating photovoltaic systems with genetic algorithms is a promising solution for energy management in Industry 4.0, promoting sustainability and industrial competitiveness, especially in regions with high solar incidence like the Amazon. The research highlights the relevance of technological innovation in the transition to a low-carbon economy.Item Transformação digital no Polo Industrial de Manaus (PIM): desenvolvimento e implementação de um sistema de Kanban eletrônico utilizando inteligência artificial para otimização e sequenciamento de produção em uma empresa de fitas do PIM(Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) ARAÚJO, Lívia Fernanda Lobão de; GUIMARÃES, Gil EduardoThis thesis discusses the development and implementation of an electronic Kanban system integrated with artificial intelligence (AI) to optimize the production sequencing process in a company located in the Industrial Pole of Manaus (PIM). The main objective of this work is to enhance operational efficiency, integrate production processes, and reduce costs through the adoption of Industry 4.0 technologies. The study explores the application of electronic Kanban as an automation tool, integrated with AI, to manage production more efficiently and transparently. The developed system aims to optimize resource allocation and supply chain management, also offering improvements in quality control and process traceability. The results demonstrate the system’s effectiveness in increasing productivity, reducing errors and rework, and enabling real-time adjustments in the production process.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.