Abnormality Detection and Life Prediction
AI-powered prediction of equipment failures and lifespan
The ‘Anomaly Detection & Lifespan Prediction Solution’ analyzes sensor data to detect early signs of equipment failure and predict lifespan. By monitoring conditions in real time, AI enhances maintenance efficiency, reduces costs, and ensures stable production.
Use Cases
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Equipment Maintenance and Replacement Timing Determination
Swift Abnormality Detection Across Manufacturing Processes
Efficient Labor and Remote Supervision for Maintenance Staff
Solution Features
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Select Appropriate Model, Including Non-ML, Based on Purpose
Effective Even With Limited Data
Leveraging Cutting-Edge Models for Optimal, Environment-Specific Deployment
Traditionally, data has been monitored visually by skilled workers and anomalies have been detected based on empirical rules, but by training the latest machine learning models on data obtained from sensors, anomalies can be detected without relying on human labor. This reduces the burden of maintenance work, such as checking huge amounts of data and long hours of monitoring.
It is possible to pick out sensor data that indicates a high degree of abnormality from the vast amount of sensor data installed on the production line.
It is possible to detect abnormalities with high accuracy even during long-term monitoring.
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