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

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2024 - 20252

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Data inicial: 2024Assunto: search.filters.subject.Artificial Intelligence

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Agora exibindo 1 - 2 de 2
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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.