<![CDATA[In additive manufacturing, mechanical vibrations generated during the printing process produce characteristic acoustic emissions, which are directly influenced by toolpath kinematics. These vibrations can adversely affect dimensional accuracy and interlayer adhesion, underscoring the need for effective process monitoring. This study investigates the correlation between specific toolpath geometries and their acoustic signatures in a Fused Deposition Modeling (FDM) 3D printer to establish a foundation for non-invasive condition monitoring. Five fundamental motion patterns—diagonal (Quadrants I-III and II-IV), horizontal, cylindrical, and vertical—were fabricated in an anechoic chamber. Acoustic emissions were captured via two microphones positioned 5 cm from the printer and analyzed in the time domain using statistical features: Root Mean Square (RMS), Kurtosis, and Crest Factor. The measured sound pressure levels ranged from 0.5 Pa to 1.5 Pa. Results indicate that the vertical toolpath yielded the lowest RMS (0.0863) and Crest Factor (5.38) values, reflecting the least intense and most stable acoustic emission. Conversely, diagonal patterns exhibited significantly higher values, denoting greater vibrational energy and transient fluctuations. These findings demonstrate a definitive influence of motion geometry on a printer's acoustic signature. The vertical pattern is identified as the most stable under the tested parameters. This research confirms that time-domain acoustic analysis is a viable technique for characterizing machine performance. Establishing this baseline correlation enables the future development of real-time, sound-based monitoring systems capable of predicting print defects and facilitating predictive maintenance, thereby enhancing the reliability and quality of additive manufacturing processes.]]>
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