What was the need?
The Challenge
The project faced several challenges, beginning with the limitations of the aging equipment. The Power Press motors, being around 30 years old, initially lacked the necessary sensors for capturing vibration or temperature data. Installing new Bluetooth vibration sensors, integrating them with the existing IoT infrastructure, and establishing a reliable data collection process required significant setup and calibration efforts.
Data preprocessing also posed challenges, particularly in distinguishing between genuine anomalies and normal vibrations caused by the press’s metalworking operations. High vibration levels during metal pressing were common and could be misinterpreted as faults, so the team had to develop filtering techniques to focus only on motor health indicators. Additionally, tuning and optimizing the machine learning models required careful consideration, especially given the complexity of the data and the need to select the most suitable algorithms. Finally, setting actionable thresholds for predictive alerts involved balancing sensitivity with the practical need to avoid false alarms, ensuring maintenance interventions were timely yet efficient.