Smart Manufacturing Powered by Cognitive Intelligence
Cognitive Anomaly Detection and Prediction organizes, structures and analyzes the massive time-series data from connected industrial machines for insights that can be turned into a wide variety of business benefits—from reducing scrap generation to enhancing product output and quality.
The key is anomaly detection—the process of identifying outliers in a normal range of performance. Historical data, current data and external influencing factors are analyzed simultaneously to establish baselines for asset performance on an ongoing basis.
When implemented through unsupervised machine-learning, anomaly detection can help predict future anomalies before they happen so you can take appropriate action. The result is assets that last longer and perform at their best—helping you avoid costly repairs and downtime.