Despite growing adoption of the Industrial Internet of Things, many businesses are still losing billions to unplanned asset downtime and equipment failures.
The issue is that many industrial enterprises simply aren’t making the most of their IIoT initiatives. They need tools to help them connect their objectives with their data and analytics framework to maximize efficiency, minimize downtime and reduce operational risk.
Cognitive anomaly detection and prediction can help IIoT companies address this issue. To learn more, view top machine learning and IoT influencer Ronald van Loon and Progress DataRPM Vice President of Product Ruban Phukan for an on-demand webinar. They will discuss how to:
Ronald van Loon
Industry Expert – Top Machine Learning and IoT Influencer
Vice President of Product
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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