Remote Control Device for the Detection and Correction of Errors in the FDM 3D Printing Process in Real Time

This project focuses on developing a remote control device for the real-time detection and correction of errors in fused deposition modeling (FDM) 3D printing. It utilizes a Raspberry Pi computer and a webcam to capture images while a neural network trained with a dataset generated by the research t...

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Bibliographic Details
Main Authors: Henry Requena, Kelvin Pozuelo, Carlos Díaz, Jean Coll
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Engineering Proceedings
Subjects:
Online Access:https://www.mdpi.com/2673-4591/83/1/12
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Description
Summary:This project focuses on developing a remote control device for the real-time detection and correction of errors in fused deposition modeling (FDM) 3D printing. It utilizes a Raspberry Pi computer and a webcam to capture images while a neural network trained with a dataset generated by the research team identifies errors such as warping, stringing, and spaghetti. Information is efficiently transmitted via MQTT, with instant notifications through Telegram and a user interface. The methodology spans from training the neural network to integrated control strategies with the remote device. Evaluation highlights high precision using confusion matrices and IoU, promising substantial improvements in industrial and critical 3D printing environments.
ISSN:2673-4591