Artigos

URI permanente para esta coleçãohttps://rigalileo.itegam.org.br/handle/123456789/5

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2021 - 20254

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Data inicial: 2021Assunto: search.filters.subject.Industry 4.0

Resultados da Pesquisa

Agora exibindo 1 - 4 de 4
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    Sistema de Visão AI-Powered para Correção de um Dispensador de Adesivos Axxon para SMT em uma Indústria do Pólo Industrial de Manaus - PIM
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) BRITO, Hallisom Luniere; BRITO, Ynara Silva Luniere; MAUES, Elvis Jardim; VIEIRA JUNIOR, Milton
    This paper presents the development and application of an intelligent system based on computer vision and artificial intelligence for monitoring and automatic correction of the adhesive application process on printed circuit boards (PCB) in the electronics industry. The adhesive application process is essential for the precise fixing of components, and eventual failures can compromise the quality and performance of the final products. To automate visual inspection and reduce the occurrence of human errors, a convolutional neural network (CNN) model trained with real images of the production line was developed, capable of identifying correct patterns and failures in the application of the adhesive. The system integrates highresolution cameras, image processing software and a control interface, enabling real-time monitoring and the execution of automatic corrective actions. The results obtained demonstrate the effectiveness of the proposed system, with a high level of accuracy in detecting faults, contributing to improving the quality of the production process and aligning with the principles of Industry 4.0. The research concludes that the adoption of intelligent systems based on computer vision represents a significant advance for quality control in the manufacturing of electronic devices.
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    Digital transformation in the Manaus Industrial Hub (PIM): development and implementation of an electronic Kanban system using Artificial Intelligence for production optimization and sequencing in a PIM tape company
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) ARAÚJO, Lívia Fernanda Lobão de; GUIMARÃES, Gil Eduardo
    This article presents the development and implementation of an electronic Kanban system with Artificial Intelligence (AI) in a company in the Manaus Industrial Estate (PIM). The research, based on Industry 4.0 principles, aimed to optimize production order sequencing and promote greater operational efficiency, process integration, and cost reduction. Using an applied and exploratory approach, quantitative and qualitative methods were used to identify bottlenecks and develop technological solutions aligned with the company’s needs. The results showed a 67% reduction in order entry time, a 22% increase in Overall Equipment Efficiency (OEE), and an 18% drop in non-conformities. This study highlights the transformative potential of digitalization and automation for PIM companies.
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    Industry 4.0 techniques applied to the improvement of the cutting process of Lithium-Ion battery terminals
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) SILVA, Linconl Fábio da; OLIVEIRA, Reinaldo Viana de; ALENCAR, David Barbosa de; NASCIMENTO, Manoel Henrique Reis; SANTOS, Alyson de Jesus dos; LEITE, Jandecy Cabral
    Industry 4.0 has revolutionized manufacturing processes with the integration of advanced technologies. This study investigates the application of Industry 4.0 techniques to optimize the cutting process of lithium-ion battery terminals. The use of smart sensors, machine learning, and automation resulted in greater precision, waste reduction, and production time optimization. The results demonstrate that the digitization and automation of the cutting process bring significant benefits to the battery industry.
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    Digital technologies review for manufacturing processes
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2021-03-31) PARENTE, Ricardo Silva; UHLMANN, Iracyanne Retto
    It is apparent the industrial processes transformations caused by industry 4.0 are in advance in some countries like China, Japan, Germany and United States. But, in return, the developing countries, as the emergent Brazil, seem like to have a long way to achieve digital era. Considering manufacturing processes as the starting point the rise of industry 4.0, this research aims to show a review about the most important technologies used in smart manufacturing, including the main challenges to implement it at Brazil. The papers were collected from Web of Science (WoS), comprising 114 articles and 2 books to underpin this study. This exploratory research resulted in the presentation of some challenges faced by Brazilian industry to join the new industrial era, such as poor technological infrastructure, besides lack of investment in technologies and training of qualified people. Even though the primary motivation of this research was to present a panorama of smart manufacturing for Brazil, this study results contributes to the most of emergent countries, bringing together general concepts and addressing practical applications developed by several researchers from the international academic community.