Edge Machine Learning for Anomaly Detection and Predictive Maintenance
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When it comes to varying tiers of maintenance strategies, reactive, preventive and predictive maintenance are all important and have their places. New tools are enhancing maintenance efficiency. More powerful and cost-effective computing combined with advancements in artificial intelligence (AI) are bringing the next era of digital transformation in manufacturing. AI coupled with predictive maintenance use parameters from the operating conditions of equipment and intelligence from application-specific inference engines at the edge to detect anomalies, which predicate a maintenance action when needed. This new technology brings decision-making and intelligence as close to the process as possible.
In this webcast our speakers, Matt Dentino and Mitsuo Baba will discuss the best ways to get started with machine learning and predictive maintenance, its numerous benefits, possible challenges along the way, why you need the right strategic partnerships for success, and much more.
- Learn the benefits of machine learning and predictive maintenance
- Understand the challenges of predictive maintenance
- Explore AI and predictive maintenance for anomaly detection
- How to get started with predictive maintenance technologies
Matt Dentino, Vice President, Client Engagement, Braintrust
Mitsuo Baba, Senior Director, IoT and Infrastructure Business Unit, Renesas Electronics Corporation
Mark Hoske, Content Manager, CFE Media and Technology