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Politeknik Negeri Lhokseumawe
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Acoustic Analysis of 3D Printing Motion Patterns for Machine Condition Monitoring Mahmud Mahmud; M. Dirhamsyah; Muhammad Rizal; Hamdani Hamdani; Azwar Azwar; Sariyusda Sariyusda; Zulfadli Zulfadli
SINTEK JURNAL: Jurnal Ilmiah Teknik Mesin Vol. 19 No. 2 (2025): SINTEK JURNAL
Publisher : Faculty of Engineering, Universitas Muhammadiyah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24853/sintek.19.2.113-131

Abstract

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.
Co-Authors Abu Bakar Ja’far Amalia Harmin Aswar Aswar Azwar Azwar Azwar Azwar Yunus Azzahari, Muhammad Bukhari Kasim Devi Mulya Sari Dirhamsyah, Muhammad Elfisa Febrianton, Adi Feri Susilwati Gunawan, Bakti Hamdani Hamdani Hamdani Hamdani, Hamdani Hilmi Hilmi Ibnu Khaldun Ichsan Ichsan M. Dirhamsyah M. Dirhamsyah M. Dirhamsyah Mhd Ridho Pratama Mizanul Ahkam Muhammad Dirhamsyah Muhammad Razi Muhammad Rizal Muhibuddin Muhibuddin, Muhibuddin Munzir Umran Nurdan Nurdan Ramadhani Rizki Faulianur Rozaliana Rozaliana RumintoSubekti Safwan, Safwan Samsul Bahri Sariyusda Sariyusda Sariyusda Sinaga, Jufri Suharyadi Pancono Zulfadli Zulfadli Zulfadli