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.
This infographic will show you how cognitive anomaly detection and prediction can help you:
Download the infographic to learn more.
DataRPM is an award-winning predictive analytics company focused on delivering the next generation predictive maintenance solutions for the Industrial IoT. DataRPM platform automates data science leveraging the next frontier in machine learning known as meta-learning, which is machine learning on machine learning. The platform increases prediction quality and accuracy by over 300% in 1/30th the time and resources delivering 30% in cost savings or revenue growth for business problems around predicting asset failures, reducing maintenance costs, optimizing inventory and resources, predicting quality issues, forecasting warranty and insurance claims and managing risks better.
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