Design and development of large scale FDM based 3D printer

Brathikan, V M; Balasubramanian, S; Kiranlal, S; Ragul, R Ravi

doi:10.1088/1742-6596/2272/1/012016

Cited by 4 publications

(2 citation statements)

References 8 publications

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“…This large-size UM structure type 3D printer has e cient printing capabilities and also offers exibility and scalability, allowing users to customize con gurations and upgrades according to their needs. It is a powerful and versatile experimental device for a variety of elds, including industrial manufacturing, educational research, and the maker community [17]. As shown in Fig.…”

Section: Experimental Methodologymentioning

confidence: 99%

An Improved 3D Printing Extrusion Defect Detection Method Based On YOLO-v8

Cao,

Fu,

et al. 2024

Preprint

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Additive manufacturing (AM) technology finds widespread use in consumer and industrial manufacturing. However, large-scale 3D printers in the manufacturing industry encounter challenges like extended printing times, high nozzle flow, and maintaining flow stability. Addressing these issues necessitates thorough research and optimization of 3D printers to enhance printing efficiency and stability. This study proposes a real-time monitoring system for identifying flow defects in large 3D printers using machine vision. The system comprises a camera capturing extrusion images, a computer processing real-time screens, and a lower computer within the monitoring system designed for real-time monitoring and correction of flow quality in large 3D printers. Defects are detected and image data captured by adjusting the extrusion speed, while an attention mechanism module optimizes the YOLOv8 model. The model is trained for deep learning using mAP50 as the performance evaluation index, achieving a mean average precision (mAP) of 92.1%. Subsequently, the optimized model is deployed on a host computer. Upon detecting flow defects, it sends commands to a Raspberry Pi, generating G-code commands to adjust extrusion speed and relay them to the 3D printer. This enables real-time monitoring and automatic calibration of the printing process. The study presents an effective solution for real-time monitoring and calibration in closed-loop processes within additive manufacturing.

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Section: Experimental Methodologymentioning

confidence: 99%

An Improved 3D Printing Extrusion Defect Detection Method Based On YOLO-v8

Cao,

Fu,

et al. 2024

Preprint

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“…Initial attempts at 3D printing were made by Dr. Kodama in 1981 and made progress in the rapid development of proto-compositions. He demonstrated the layer-by-layer assembly process to create a photosensitive rubber that was polymerized by UV light [1]. In the article, we will focus on the construction of a printer that creates three-dimensional objects by successively applying thin layers of heated thermoplastic material unrolling from a coil.…”

Section: Introductionmentioning

confidence: 99%

Design and analysis of equipment intended for the production of prototypes

Kusa,

Holubek,

Bocak

2024

J. Phys.: Conf. Ser.

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The article deals with the design of a device working on the principle of Fused Deposition Modeling - FDM and its peripherals. Among the most important performing activities of the designer is the analysis of the proposed model with regard to the strength and the resulting accuracy of the created three-dimensional object. The input requirements that the proposed device should meet were defined. Based on these criteria, a numerical and strength analysis was developed using the FEM finite element method. The simulation was carried out on the basis of the hypothesis of shear stress transformation work, which is among the most accurate for the tough materials used. The analysis monitored and evaluated the deformations in the extreme positions where the largest deformations were expected to occur.

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The Role of 3D Printing Technologies in Soft Grippers

Xin,

Zhou,

Bark

et al. 2023

Advanced Materials

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Soft grippers are essential for precise and gentle handling of delicate, fragile, and easy‐to‐break objects, such as glassware, electronic components, food items, and biological samples, without causing any damage or deformation. This is especially important in industries such as healthcare, manufacturing, agriculture, food handling, and biomedical, where accuracy, safety, and preservation of the objects being handled are critical. This article reviews the use of 3D printing technologies in soft grippers, including those made of functional materials, nonfunctional materials, and those with sensors. 3D printing processes that can be used to fabricate each class of soft grippers are discussed. Available 3D printing technologies that are often used in soft grippers are primarily extrusion‐based printing (fused deposition modeling and direct ink writing), jet‐based printing (polymer jet), and immersion printing (stereolithography and digital light processing). The materials selected for fabricating soft grippers include thermoplastic polymers, UV‐curable polymers, polymer gels, soft conductive composites, and hydrogels. We conclude that 3D printing technologies revolutionize the way soft grippers are being fabricated, expanding their application domains and reducing the difficulties in customization, fabrication and production.This article is protected by copyright. All rights reserved

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Design and development of large scale FDM based 3D printer

Cited by 4 publications

References 8 publications

An Improved 3D Printing Extrusion Defect Detection Method Based On YOLO-v8

An Improved 3D Printing Extrusion Defect Detection Method Based On YOLO-v8

Design and analysis of equipment intended for the production of prototypes

The Role of 3D Printing Technologies in Soft Grippers

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