Anomaly Detection for Cognitive Intelligence

Today’s industrial organizations are often tasked with objectives that are seemingly at odds with each other. They need to increase productivity while reducing machine failure or enhance product quality while speeding up time to market. Achieving these goals simultaneously can be incredibly challenging — if not impossible.How does one work around this dilemma? The trick lies in cognitive anomaly detection and prediction, which is a process that leverages unsupervised learning (cognitive computing) and pattern recognition to quickly and accurately identify the anomalies hidden in your Industrial Internet of Things data. The use of machine learning algorithms minimizes the appearances of false alarms