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 With "reactive maintenance," where repairs are made each time equipment fails, the operational rate decreases. In "preventive maintenance," where regular replacements are made including equipment that is still usable, costs may increase. If "predictive maintenance" can forecast the timing of equipment failures, replacements can be made at the moment abnormal signs are detected, allowing for a balanced operation between costs and operational rates. "Predictive maintenance" was technically challenging, but it has become feasible with the advent of AI and deep learning.
