Abstract
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.
Highlights
The past three decades have witnessed the rapid growth of Additive Manufacturing (AM)technologies
We proposed a new Acoustic Emission (AE) feature extraction method, namely relative similarity, to represent the differences between two AE probability distributions more precisely
The results suggest that the relative similarity is better than the instantaneous skewness in filament breakage detection
Summary
The past three decades have witnessed the rapid growth of Additive Manufacturing (AM). During the last five years, AM has gained widespread attention from the academic community, and the public. Companies across the globe are using AM to reduce time-to-market, improve product quality and reduce the cost to manufacture products. Polymer-based AM techniques are being used in a wide range of part applications including automotive, aerospace and medical devices [1]. The most widely-used and rapidly-growing AM technologies are extrusion deposition processes such as Fused Deposition Modeling (FDM), Fused. Filament Fabrication (FFF) and Melt Extrusion Manufacturing (MEM) [2]. While the use of AM has been growing, numerous challenges impede its more widespread adoption and commercialization [3]
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