PENERAPAN PREDICTIVE MAINTENANCE UNTUK MENDETEKSI CACAT RODA GIGI LEBIH DINI

Terkisah Alif Rizky (Politeknik Manufaktur Negeri Bangka Belitung)
Wahyu Dirgantara (Politeknik Manufaktur Negeri Bangka Belitung)
Ariyanto Ariyanto (Politeknik Manufaktur Negeri Bangka Belitung)
Ramli Ramli (Politeknik Manufaktur Negeri Bangka Belitung)

Prosiding Seminar Nasional Inovasi Teknologi Terapan
Vol. 6 No. 1 (2026): Prosiding Seminar Nasional Inovasi Teknologi Terapan

Gear transmission systems are critical components in industrial machinery that are susceptible to degradation due to continuous operational loads. Early detection of gear damage is essential to prevent catastrophic failure and minimize production downtime. This study aims to implement a predictive maintenance system based on vibration analysis and machine learning to detect and classify the conditions of spur gears and helical gears. The damage scenarios tested include wear, normal operating conditions, and structural damage such as chipping or fractures. Vibration data were acquired using a triaxial accelerometer on a gearbox test rig.