In-Situ Monitoring and Diagnosing for Fused Filament Fabrication Process Based on Vibration Sensors

Abstract

Fused filament fabrication (FFF) is one of the most widely used additive manufacturing (AM) technologies and it has great potential in fabricating prototypes with complex geometry. For high quality manufacturing, monitoring the products in real time is as important as maintaining the FFF machine in the normal state. This paper introduces an approach that is based on the vibration sensors and data-driven methods for in-situ monitoring and diagnosing the FFF process. The least squares support vector machine (LS-SVM) algorithm has been applied for identifying the normal and filament jam states of the FFF machine, besides fault diagnosis in real time. The identification accuracy for the case studies explored here using LS-SVM is greater than 90%. Furthermore, to ensure the product quality during the FFF process, the back-propagation neural network (BPNN) algorithm has been used to monitor and diagnose the quality defects, as well as the warpage and material stack caused by abnormal leakage for the products in-situ. The diagnosis accuracy for the case studies explored here using BPNN is greater than 95%. Results from the experiments show that the proposed approach can accurately recognize the machine failures and quality defects during the FFF process, thus effectively assuring the product quality.

Development of an Automatic Image Cropping and Feature Extraction System for Real-Time Warping Monitoring in 3D Printing

“…Li et al [29] developed an in-situ FFF 3D Printing monitoring system that monitors both the state of the printer and the quality of the print with vibration sensors. As Figure 4 indicates, four vibration sensors are attached to the FFF 3D printer: one is attached to the build platform, the other three are attached to the extruder.…”

In-Situ Monitoring of Layer-Wise Fabrication by Electrical Resistance Measurements in 3D Printing

“…Several insitu techniques already exist for quality monitoring in FDM printing. Techniques are, among others, based on optical scanning [13], computer vision [14], acoustics [15], vibrations [16], strain [17], rheological [18] and thermal measurements [19]. However, to the best of the author's knowledge an in-situ technique for monitoring the electrical properties has not yet been proposed.…”

Experimental study of fabrication‐induced residual strains and distortions in polymeric square plates built using fused deposition modeling process

“…Important processing parameters such as layer thickness, part build orientation, raster angle, road width, air gap, printing temperature, and layout of parts on the worktable have been studied, and their effects on the printed samples' mechanical properties have been reported in various research works 4–6 . In addition, experimental efforts have been directed towards measuring the residual stresses in FDM parts 7 or monitoring the printing procedure using thermocouples, 8,9 IR cameras, 10 vibration sensors, 11 and fiber Bragg grating (FBG) sensors 8,12 . Characteristically, Casavola et al 7 employed the hole‐drilling method to measure residual stresses in FDM parts combined with electronic speckle pattern interferometry.…”