Polymers are being used in a wide range of Additive Manufacturing (AM) applications and have been shown to have tremendous potential for producing complex, individually customized parts. In order to improve part quality, it is essential to identify and monitor the process malfunctions of polymer-based AM. The present work endeavored to develop an alternative method for filament breakage identification in the Fused Deposition Modeling (FDM) AM process. The Acoustic Emission (AE) technique was applied due to the fact that it had the capability of detecting bursting and weak signals, especially from complex background noises. The mechanism of filament breakage was depicted thoroughly. The relationship between the process parameters and critical feed rate was obtained. In addition, the framework of filament breakage detection based on the instantaneous skewness and relative similarity of the AE raw waveform was illustrated. Afterwards, we conducted several filament breakage tests to validate their feasibility and effectiveness. Results revealed that the breakage could be successfully identified. Achievements of the present work could be further used to develop a comprehensive in situ FDM monitoring system with moderate cost.
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