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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Filtros

2024 - 20253

Configurações

Assunto: search.filters.subject.OEE

Resultados da Pesquisa

Agora exibindo 1 - 3 de 3
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    Uso da Ferramenta OEE para Otimizar o Processo de Fabricação de Placas de Circuito Impresso no Processo SMT
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) MEDEIROS, Gelson Ricardo Martins; SANTOS, Eliton Smith dos; ALMEIDA, Luiz Fernando Correia de Almeida
    This dissertation addresses the application of the Overall Equipment Effectiveness (OEE) metric in the Surface Mount Technology (SMT) process to optimize production efficiency in a company located in the Manaus Industrial Hub. The study identifies the main losses affecting the printed circuit board assembly line, classifies these losses, and proposes improvement actions based on the Total Productive Maintenance (TPM) methodology. The methodology includes a case study, data collection from production lines, expert interviews, and practical application of performance indicators. The results demonstrate that the use of the OEE tool, combined with corrective and preventive measures, can enhance SMT line efficiency and significantly reduce losses related to downtime, speed, and quality.
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    Eficiência Produtiva em Linhas SMT: Aplicação da Métrica OEE e Estratégias de Melhoria na Indústria Eletroeletrônica da Zona Franca de Manaus
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2025) MEDEIROS, Gelson Ricardo Martins; ALMEIDA, Luiz Fernando Correia de; SANTOS, Eliton Smith dos
    This article presents the results of an applied study on production efficiency in a Surface Mount Technology (SMT) assembly line within the electronics manufacturing sector of the Manaus Free Trade Zone. Through the application of the Overall Equipment Effectiveness (OEE) metric, the study aimed to diagnose operational bottlenecks and propose targeted interventions using tools such as the Ishikawa Diagram and SMED method. Data collected between January and June 2023 revealed significant losses in availability and performance, leading to an OEE of only 22.4%—far below the world-class benchmark of 85%. Corrective actions including predictive maintenance, shift reorganization, and digital control via MES contributed to reducing downtime and improving operational governance. The study concludes that OEE is not merely a technical metric but a strategic tool for organizational transformation and Industry 4.0 integration.
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    Estudo de Caracterização da Eficiência Produtiva nas Indústrias de Montagem de Eletroeletrônicas do Polo Industrial de Manaus por Meio do Cálculo do OEE - Caso de Estudo de Automação
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2024) MONTEIRO, Isabela Zanotto; MARINELLI FILHO, Nelson; GUIMARÃES, Gil Eduardo; CORREA, Geraldo Nunes; FERREIRA, Matheus Rissardi; MARINELLI FILHO, Nelson
    This study presents the implementation of Industry 4.0 enabling technologies, with an emphasis on the use of Digital Twins and the automation of OEE (Overall Equipment Effectiveness) calculation, applied to an electro-electronic assembly line at the Manaus Industrial Pole (PIM). The objective was to develop a solution capable of identifying, in real time, the times and reasons for production stoppages, aiming to optimize industrial processes and reduce operational costs. Data were collected through IoT sensors installed on production lines, integrated into a digital platform that virtually replicated the factory plant in a Digital Twin system. OEE was automatically calculated based on three main indicators: Availability, Performance, and Quality. Simulations in the virtual environment identified production bottlenecks and allowed predictive actions to prevent failures and optimize machine performance. The results, obtained over 80 days of monitoring, showed an evolution in productive efficiency indicators, with a reduction in unplanned downtime, dynamic adjustment of production parameters, and improvement in product quality, positively impacting industrial sustainability and energy efficiency.