Monografia_Mec_Industrial

URI permanente para esta coleçãohttps://ri.ifam.edu.br/handle/4321/966

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Projeto de uma secadora de filamentos com foco em baixo custo
(2025-04-23) Almeida, Natã da Silva; Santos, Renan Cavalcante; http://lattes.cnpq.br/6930748017205035; Souza, Daniel Fonseca de; http://lattes.cnpq.br/4043793492782488; Gadelha, Vitor Fernando de Souza; http://lattes.cnpq.br/4283627740352016
This work aims to develop a low-cost filament dryer designed for 3D printer users who face print quality issues due to excessive ambient humidity. The research is particularly relevant for regions with high humidity levels, such as the Amazon, where climate conditions affect filament preservation, resulting in 3D printing failures like bubbles, fractures, and poor surface finish. The proposed dryer seeks to meet this demand by offering an affordable solution to maintain filament quality, extend its lifespan, and prevent damage caused by moisture absorption. The project focuses on using low-cost materials and technologies, ensuring economic feasibility and ease of construction. The innovation of this work lies in adapting to local needs, providing a practical, efficient, and accessible solution for the 3D printing community in the Amazon region. The developed dryer successfully removed moisture from the filaments during testing and validation.
Sistema de inspeção de bateria de lítio em placas eletrônicas: uma proposta a partir da integração de CLP e aprendizado de máquina
(2025-09-16) Dutra, João Victor Pontes; Ribeiro, João Bernardo Aranha; http://lattes.cnpq.br/9027441032059817; Gadelha, Vitor Fernando de Souza; http://lattes.cnpq.br/4283627740352016; Ribeiro, Ewerton Andrey Godinho; http://lattes.cnpq.br/0187470129136467
The objective of this work is to develop a lithium battery inspection system based on the integration of Programmable Logic Controllers and Machine Learning, identifying advantages, disadvantages, and challenges associated with meeting the needs of industrial facilities. The project seeks to use low-cost materials and technologies, ensuring its economic viability and ease of construction. The innovation of the work lies in the adaptation of organizational needs, using Industry 4.0 tools, providing a practical, efficient, and assertive solution. Thus, the proposed system aims to address these aspects, offering an accessible solution for detecting assembly, optimization, and quality failures. The system inspection is based on a supervised learning that detects the battery via webcam and then compares the captured image with the model created from the OK and NG datasets. Therefore, the difference between the two results in an approved or rejected result for the part. The developed system performed well in its inspections during testing and validation. In addition, the work designated the observation of this integration in other segments, instigating opportunities and improvements for effective advancement. Therefore, the study concluded that, despite the significant challenges to implementing AM in PLCs, the integration shows promise for optimizing operational efficiency, flexibility, data transmission, cost reduction, and decision-making support in companies with limited resources and a need for modernization.