Artigos
URI permanente para esta coleçãohttps://rigalileo.itegam.org.br/handle/123456789/5
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Item Application of Deep Neural Network in Intelligent System with Production Dashboard(Instituto de Tecnologia e Educação Galileo da Amazônia, 2022) RAMOS JUNIOR, Juarez da Silva; LEITE, Jandecy Cabral; GOMES, Marivan Silva; PAULA, Railma Lima de; CARVALHO, Michael da Silva; SILVA, Ítalo Rodrigo Soares; SIQUEIRA JUNIOR, Paulo Oliveira; PARENTE, Ricardo Silva; MIRANDA, Luís Gabryel dos Santos; LEITE, Jandecy CabralLean Manufacturing is a strategic methodology aimed at reducing production waste, ensuring product quality, and optimizing delivery times. However, many electronic meter manufacturing companies lack the necessary technologies to effectively implement this methodology. This study proposes the development of an Intelligent Lean Manufacturing System based on the requirements of a Manufacturing Execution System (MES), utilizing technologies such as Artificial Intelligence, the Internet of Things, and Embedded Systems. The system enables real-time decision-making for production control and management, reducing costs and improving product quality.Item System for Analysis, Simulation and Implementation of Improvements in the Air Conditioning Manufacturing Process(Instituto de Tecnologia e Educação Galileo da Amazônia, 2022) CASTRO, Diego Alexandre de Lima LEITE, Jandecy Cabral; LEITE, Jandecy CabralThis study presents proposals for improvements in an air conditioner assembly line at a factory in the Manaus Industrial Hub. The research details the production process and evaluates factors hindering production, aiming to increase capacity, quality, efficiency, and waste reduction. Company documentary records and simulation tools (Plant Simulation) were used to identify bottlenecks and propose solutions. The new implemented layout provided a sustainable competitive advantage, improved employee training, and access to new automation technologies.Item Implementation of SMED Methodology to Reduce the Setup Time in a SMT Production Line(Instituto de Tecnologia e Educação Galileo da Amazônia, 2023) DANTAS, Jorginaldo Dibo LIMA, Alexandra Amaro de; LEITE, Jandecy CabralThe overall objective is to implement the Single Minute Exchange of Die (SMED) methodology to reduce the setup time (model change) in an electronics factory in Brazil. The research was carried out at a company in the electronics segment, located in the Industrial Pole of Manaus (PIM). Using a cause-and-effect diagram, it was verified that machines, labor, method, and material are the main causes for the high setup time. The initial SMED action plan defined eleven actions to reduce the line setup time. The implementation of the SMED method resulted in a 64% reduction in setup time, bringing significant productivity and efficiency improvements to the analyzed SMT line.Item Optimization of the Manual Insertion Process of Electric Motor Winders Using Lean Manufacturing Techniques(Instituto de Tecnologia e Educação Galileo da Amazônia, 2023) SOUZA, Renê Brito de LEITE, Jandecy Cabral; LEITE, Jandecy CabralDuring the manual insertion process analysis in electric motor production, process losses were identified. Using Lean Manufacturing tools and data collection, gaps in line balancing were mapped, resulting in low efficiency and desaturation in the insertion process. This study proposes the application of computer simulation and industrial layout restructuring based on NR-12 safety standards, in addition to implementing improvements such as the use of the spaghetti diagram and Kaizen techniques. The results indicate an average reduction of 30% in handling time, ergonomic improvements, better organization of the production space, and a reduction in intermediate inventories, consolidating an efficient and replicable model in other industrial units.Item Uso de Ferramentas de Lean Manufacturing para Identificar os Fatores Geradores de Impactos Ambientais Associados a Desperdícios de Produtividade na Fabricação de Uniformes - Um Estudo de Caso em uma Indústria de Confecção de Uniformes no Polo Industrial de Manaus(Instituto de Tecnologia e Educação Galileo da Amazônia, 2023) MELO, Cidarta Gautama de Souza; LIMA, Alexandra Amaro de; LEITE, Jandecy CabralThis article presents a study that demonstrates the applicability of Lean Manufacturing tools in identifying environmental impact factors in a clothing industry located in the municipality of Manaus, Amazonas. The focus of the study was on the company's production cells, specifically Cell 1, in the manufacturing of pants and PPEs. The results of the first part of the study revealed that a detailed analysis of the production flow through Value Stream Mapping (VSM) allowed for the identification of non-value-added processes that contributed to waste and environmental impacts, such as improper use of plotting papers, fabric waste in the cutting sector, and electricity usage in the sewing sector. The second part of the study highlighted the challenges encountered in the company's production process, including unplanned downtime, unbalanced operations, and interruptions for the insertion of different products on the same production line. The application of Lean tools such as Takt Time, TRF, Continuous Flow, Heijunka, and Standardized Work was identified as crucial in improving operational efficiency and reducing waste, thereby contributing to the minimization of environmental impacts. The overall results of the study showed that the application of Lean Manufacturing tools allowed for the identification of processes associated with invisible environmental impact factors, resulting in a significant reduction in waste indicators, especially in delivery, intermediate stocks, and rework rates. Additionally, there was a noticeable decrease in energy usage and textile waste disposal, generating a positive environmental impact. The study also presented a framework of conditional indicators and goals, revealing significant progress towards more efficient and sustainable production, with an overall reduction of 45% in waste indicators and established goals of at least 20% reduction in each indicator related to environmental impacts. This study demonstrates the effectiveness of Lean Manufacturing approaches in promoting more sustainable practices in the clothing industry.