Desain dan Pengujian Predictive Maintenance Agitator Berbasis Internet of Things untuk Sistem Pengolahan Air - Aris Puja Widikda; Angga Debby Frayudha (Infotekmesin, 2026)
Agitators play an important role in the mixing, coagulation, and flocculation processes in the water treatment industry. An Internet of Things (IoT)-based predictive maintenance system was designed for early detection of agitator anomalies, including shaft imbalance/misalignment, bearing degradation, slip/RPM drop due to overload, and motor overheating. The system uses ESP32 as an edge device with an SW-420 (vibration pulse) sensor, a DS18B20 (motor temperature) sensor, and a Hall effect sensor (RPM). Data is sent via MQTT to the cloud server for real-time visualization on the dashboard. Validation against the reference instrument showed a MAPE of 0.518% and a correlation of 0.999. Anomaly warnings are triggered when the temperature is 69.5–70°C (critical 72°C) and vibration exceeds the 3σ threshold (warning 410 pulses; critical 550 pulses).