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What is Digital Twin for 3D Printer Fault Detection about?

This document presents a novel approach for fault detection in Fused Deposition Modelling (FDM) 3D printers using a Lightweight Convolutional Neural Network (LCNN) and Digital Twin (DT) technology. The LCNN model effectively monitors and detects faults based on sensor data, achieving a high F1-Score of 0.9981, while the DT environment allows for real-time monitoring and control of the printing process. This research aims to enhance the reliability and efficiency of smart additive manufacturing by minimizing

Author

AdDie ParaMartha

Language

EN