Livros e capítulo

URI permanente para esta coleçãohttps://rigalileo.itegam.org.br/handle/123456789/6

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2024 - 20255

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Tem arquivos: SimAssunto: search.filters.subject.Indústria 4.0

Resultados da Pesquisa

Agora exibindo 1 - 5 de 5
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    Industrial Engineering and Operations Management
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) JUNIOR, Milton Vieira; LEITE, Jandecy Cabral
    The 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.
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    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.
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    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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    Business Intelligence as an Integration Tool for Fault Detection of the Board Assembly Process
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) CAMPOS, Paola Souto; LEITE, Jandecy Cabral
    The plate assembly process in the analyzed company has a stipulated goal of 2000 plates per day, and 10% of this production has failures, compromising the management's defined goals. Given this issue, the present study aims to implement an intelligent system for identifying and correcting failures in the board assembly process, based on Business Intelligence (BI), aligned with Industry 4.0 practices. The methodology included Process Mapping and Requirements Analysis for the Implementation of the Integrated System. The system enabled faster and more effective communication with other production process systems, ensuring accurate information for performance optimization and data security. The implementation of this intelligent failure detection system represented a significant step towards Industry 4.0 evolution.
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    Transformações Digitais e Indústria 4.0 no Polo Industrial de Manaus: Desafios e Inovações
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) GUIMARÃES, Gil Eduardo; MARINELLI FILHO, Nelson; LEITE, Jandecy Cabral; NASCIMENTO, Manoel Henrique Reis
    Industry 4.0 introduces a significant transformation in the production sector, integrating technologies such as IoT, artificial intelligence, and big data to create intelligent and flexible operations. This study investigates the challenges and opportunities of implementing these technologies in the Manaus Industrial Hub (PIM), considering factors such as infrastructure, organizational competencies, and cultural resistance. The research proposes a strategic roadmap divided into three phases for the adoption of these technologies, addressing training, automation, and artificial intelligence implementation. The study concludes that transitioning to Industry 4.0 requires integrated strategies that consider technical and cultural aspects, contributing to global competitiveness and the region's sustainable development.