Predictive maintenance with AI: Bearing anomaly diagnosis AI - vibGazer

Strongly supporting bearing maintenance with the introduction of AI, contributing to the creation of factories that never stop.

vibGazer can perform high-precision normal and abnormal judgment. <Overview> The bearing abnormality diagnosis AI 'vibGazer' focuses on the vibration data of bearings in rotating drive systems such as motors. The AI model quickly detects signs of abnormalities and notifies you before the equipment fails and stops. <What vibGazer can do> - High-precision normal and abnormal judgment - Estimation of abnormal types - Predictive maintenance: forecasting failure timing Using "reactive maintenance," where repairs are made each time equipment fails, reduces operational efficiency. On the other hand, "preventive maintenance," which involves regular replacements including still usable equipment, can lead to increased costs. If "predictive maintenance" can forecast the timing of equipment failures, it allows for equipment replacement at the moment abnormal signs are detected, enabling a balanced operation between costs and operational efficiency. "Predictive maintenance" was technically challenging, but it has become feasible with the advent of AI and deep learning.

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