面向智能增材制造(AM)的熔融沉积方法(FDM)打印机的数字化

Zhen Qi Chee, Zi Jie Choong, Wai Leong Eugene Wong
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引用次数: 2

摘要

Covid-19期间的恐慌性购买导致农民提高了产量。然而,农用设备的购买成本很高。因此,一些农民利用增材制造(AM)以低成本制造农具。然而,在增材制造中缺乏现场监控来停止打印故障部件可能会浪费材料和时间。因此,本研究旨在部署一种低成本的智能远程监控系统,使用OctoPrint和Node-red将3D打印机和Teachable Machine集成在一起,并训练模型先发制人地检测打印错误。结果是令人满意的,因为当相机检测到缺陷时,3D打印机停止了,精确度为75%。此外,用户可以通过开发的无代码平台轻松定制模型,以增强系统的通用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Digitization of Fused Deposited Methods (FDM) Printer for Smart Additive Manufacturing (AM)
The panic buying during Covid-19 caused farmers to amped-up production. However, farm equipment is costly to purchase. Therefore, some farmers utilized Additive Manufacturing (AM) to manufacture farming tools at low cost. However, the lack of in-situ monitoring in AM to stop printing failed parts can waste materials and time. Thus, this research aims to deploy a low-cost smart remote monitoring system using OctoPrint and Node-red to integrate a 3D printer and Teachable Machine and train a model to pre-emptively detect print errors. The result was satisfactory as the 3D printer stopped when the camera detected a defect with 75% accuracy. Furthermore, the user can easily customize the model to enhance the system versatility via the developed code-free platform.
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